Month: July 2023

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Stonegate Investment Group Increases Stake in MongoDB, Inc. as Company Continues to Thrive

July 4, 2023

In a surprising move that has left the investment world intrigued, Stonegate Investment Group LLC has significantly enhanced its holdings in MongoDB, Inc. (NASDAQ: MDB). As per the recent disclosure made to the SEC, Stonegate Investment Group LLC purchased an additional 526 shares during the first quarter, equating to a remarkable 9.6% increase. The total number of shares owned by the company now stands at 6,028, with a valuation of approximately $1,405,000 at the end of the most recent quarter.

The Rise and Reach of MongoDB:
MongoDB, Inc. is a trailblazer when it comes to providing a general-purpose database platform on a global scale. With its cutting-edge solutions like MongoDB Atlas and MongoDB Enterprise Advanced, the company caters to customers seeking comprehensive cloud-based database-as-a-service options as well as commercial-grade servers for enterprises operating in various environments including hybrid setups. Additionally, MongoDB offers Community Server—a freely downloadable version that supports developers in their initiation into utilizing MongoDB’s feature-rich database capabilities.

Financial Snapshot and Market Standing:
On Tuesday morning trading on NASDAQ, MDB stocks opened at $411.42—an impressive figure suggesting positive market sentiment surrounding the company. Over the past year prior to this reference date, MDB stock traded between its lowest price at $135.15 and reached its peak at $418.70—an astounding achievement showcasing significant growth potential within this period.

Analyzing Important Metrics:
While evaluating fundamental aspects pertaining to MongoDB’s financial well-being, key ratios play a pivotal role in gauging efficiency and stability. The company has demonstrated commendable liquidity through quick ratios that align with current ratios both standing at an impressive figure of 4.19—a clear indicator of healthy working capital management practices by maintaining adequate short-term assets to meet obligations. MongoDB’s debt-to-equity ratio, at 1.44, suggests acceptable levels of leverage in the company’s capital structure without raising concerns about excessive debt burden.

Moving Averages signaling Steady Growth:
Technical analysts have been closely monitoring MDB stock movements using the 50-day moving average and the 200-day moving average. As of this date, the former stood at $316.10, while the latter was recorded at $247.56—a clear indication of progressive growth in recent months.

Conclusion:
Stonegate Investment Group LLC’s decision to strengthen its holdings in MongoDB, Inc. demonstrates confidence in the company and its impressive performance within a highly competitive market. MongoDB’s focus on innovation, providing versatile database solutions for different customer segments, along with stable financial indicators and consistent stock performance, positions it as a promising player in the technology industry.

As investors ponder the significance of Stonegate Investment Group LLC’s move, uncertainties surrounding MongoDB are replaced by a sense of optimism for its future prospects as it continues to disrupt traditional database practices and adapt to evolving business needs worldwide

MongoDB: A Rising Star in the Database Industry

July 4, 2023 – MongoDB: A Rising Star in the Database Industry

In recent months, hedge funds and institutional investors have taken notice of MongoDB, Inc, a global general-purpose database platform provider. These investors have been actively buying and selling shares of MongoDB stock, signaling their confidence in the company’s future prospects.

Cherry Creek Investment Advisors Inc. raised its position by 1.5% during the fourth quarter, now owning 3,283 shares valued at $646,000 after purchasing an additional 50 shares. Allworth Financial LP followed suit by increasing its stake by 12.9%, now owning 508 shares valued at $100,000 after purchasing an additional 58 shares.

Cetera Advisor Networks LLC also increased its position with a rise of 7.4% during the second quarter. They now own 860 shares valued at $223,000 after acquiring an additional 59 shares. First Republic Investment Management Inc., on the other hand, boosted its holding by 1.0%, amounting to a total of 6,406 shares worth $1,261,000.

Furthermore, Janney Montgomery Scott LLC showed faith in MongoDB by raising its position by 4.5%, owning 1,512 shares valued at $298,000 after purchasing an additional 65 shares.

These percentages indicate not only growing interest in MongoDB but also reflect the healthy state of affairs for the company with strong investor backing from hedge funds and institutional investors who control a significant portion of their stock at approximately 89.22%.

This upward trend indicates that influential financial institutions believe in MongoDB’s potential to deliver great returns to investors.

In terms of insider trading activity within MongoDB, Director Dwight A. Merriman has played a prominent role lately. Merriman sold a total of 2,000 company shares on May 4th for an average price of $240 per share—amounting to a substantial transaction of $480,000. Following this sale, Merriman retained ownership of 1,223,954 shares valued at approximately $293,748,960.

Another noteworthy transaction took place on June 1st when Merriman sold 3,000 shares of the company’s stock at an average price of $285.34 per share—totaling $856,020. After this sale, Merriman retained ownership of 1,219,954 shares valued at around $348,101,674.

Over the last 90 days alone, insiders have sold an impressive 50,050 company shares worth a total of $13,942,694. These insider transactions hold significant weight in terms of market sentiment and confidence in the company’s growth trajectory.

MongoDB offers several database solutions that cater to different customer needs. Their flagship product is MongoDB Atlas—a hosted multi-cloud database-as-a-service solution that allows businesses to leverage database technology without the need to invest in costly infrastructure or maintenance.

For enterprise customers who prefer on-premise or hybrid environments, MongoDB offers MongoDB Enterprise Advanced—a commercial database server that provides robust features tailored for large organizations.

Additionally, developers can get started with MongoDB using the free Community Server version—the perfect choice for those looking to learn and experiment with MongoDB’s functionality.

In terms of financial performance, MongoDB recently reported its quarterly earnings data on June 1st. The company surpassed analysts’ consensus estimates by posting earnings per share (EPS) of $0.56 for the quarter—surpassing expectations by an impressive margin of $0.38.

It’s worth noting that MongoDB had a negative net margin of 23.58% but managed to exhibit revenue growth with a total revenue figure of $368.28 million during the quarter—which exceeded analyst estimates predicting $347.77 million in revenue.

Moving forward into the current fiscal year and beyond, equities analysts have voiced their opinions on MDB. Several analysts, including Needham & Company LLC, Oppenheimer, The Goldman Sachs Group, Piper Sandler, and Morgan Stanley, have raised their target prices for MongoDB shares—an indication of their positive outlook on the company’s potential.

MongoDB’s stock has received an average rating of “Moderate Buy,” with analysts predicting a consensus target price of $366.30.

As we look ahead into the future, it is quite clear that MongoDB is a rising star in the database industry. With growing investor interest, strong financial performance, innovative product offerings, and positive analyst sentiments, MongoDB appears to be well-poised to continue its upward trajectory and deliver value to its stakeholders.

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NoSQL Database Market is expected to reach USD 36.46 billion by 2029, with a CAGR of 30% between 2023 and 2029.

NoSQL Database Market Overview

The total global market for the NoSQL Database Market was valued at USD in 2022 and is expected to grow at a CAGR of # percent over the forecast period to reach USD by 2029. The report analyzed by Maximize Market Research, on the NoSQL Database market, covers an extensive regional analysis and competitive landscape.

Click To get FREE SAMPLE PDF (Including Full TOC, Table Figures) : https://www.maximizemarketresearch.com/request-sample/97851 

NoSQL Database Market Report Scope and Research Methodology

The detailed analysis of segments provides clear information on the NoSQL Database Market potential. The report provides investors with a complete insight into the NoSQL Database industry’s future, as well as the elements that are expected to affect the market positively and negatively. For the competitive analysis, the report includes the market leaders, followers and new entrants in the NoSQL Database Industry with information on strategies, revenue, partnership, joint ventures, etc.

The NoSQL Database Market report provides a qualitative and quantitative analysis of market size, price, demand, mergers and acquisitions, supply chain, investment and expansion plans by key competitors, and predictions. For the competitive analysis, the report involves the market leaders, followers and new entrants in the NoSQL Database Industry with information on strategies, revenue, partnership, joint ventures, etc. The bottom-up approach was used to estimate the NoSQL Database Market size. To collect the data for the NoSQL Database Market report, primary and secondary data collection methods were used. To provide the strengths and weaknesses of the NoSQL Database’ key players, the SWOT analysis was used. PESTLE was used to present the potential impact of the macroeconomic and micro-economic factors affecting the NoSQL Database industry.

NoSQL Database Market Regional Insights

The report includes a thorough analysis of all the factors, market size, growth rate, and import and export in regions. To understand the NoSQL Database market status in several countries, the regional analysis is used in the report. The NoSQL Database market is broadly segmented into North America, Europe, Asia Pacific, Latin America, the Middle East, and Africa.

NoSQL Database Market Segmentation

by Type

Key-Value Store
Document Database
Column Based Store
Graph Database

by Application

Data storage
Mobile apps
Web apps
Data analytics
Others

The NoSQL database industry is driven by an increase in demand for e-commerce and online applications, which adds to total market demand. Internet traffic data is regularly collected by e-commerce software. They keep a close eye on the digital imprint of any login activity and respond appropriately. A

by Industry Vertical

Retail
Gaming
IT
Others

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NoSQL Database Market Key Players

1. DynamoDB
   2. ObjectLabs Corporation
   3. Skyll
   4. InfiniteGraph
   5. Oracle
   6. MapR Technologies, Inc.
   7. Apache Software Foundation
   8. Couchbase
   9. Basho Technologies
   10.Aerospike Inc.
   11.IBM Corporation
   12.MarkLogic Corporation
   13.Neo technology Inc.
   14.Hypertable Inc.
   15.Cisco Systems Inc.
   16.Objectivity Inc.
   17.Oracle Corporation
   18.Microsoft Corporation

Key questions answered in the NoSQL Database Market are:

• What is NoSQL Database?
• What was the NoSQL Database market size in 2023?
• What is the growth rate of the NoSQL Database Market?
• Which are the factors expected to drive the NoSQL Database market growth?
• What are the different segments of the NoSQL Database Market?
• What growth strategies are the players considering to increase their presence in NoSQL Database?
• What are the upcoming industry applications and trends for the NoSQL Database Market?
• What is the demand pattern of the NoSQL Database Market?
• What major challenges could the NoSQL Database Market face in the future?
• What segments are covered in the NoSQL Database Market?
• Who are the leading companies and what are their portfolios in NoSQL Database Market?
• What segments are covered in the NoSQL Database Market?
• Who are the key players in the NoSQL Database market?

Key Offerings:

• Past Market Size and Competitive Landscape (2018 to 2022)
• Past Pricing and price curve by region (2018 to 2022)
• Market Size, Share, Size & Forecast by different segment | 2023−2029
• Market Dynamics – Growth Drivers, Restraints, Opportunities, and Key Trends by Region
• Market Segmentation – A detailed analysis by segment with their sub-segments and Region
• Competitive Landscape – Profiles of selected key players by region from a strategic perspective
  • Competitive landscape – Market Leaders, Market Followers, Regional player
  • Competitive benchmarking of key players by region
• PESTLE Analysis
• PORTER’s analysis
• Value chain and supply chain analysis
• Legal Aspects of Business by Region
• Lucrative business opportunities with SWOT analysis
• Recommendations

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Maximize Market Research is a multifaceted market research and consulting company with professionals from several industries. Some of the industries we cover include medical devices, pharmaceutical manufacturers, science and engineering, electronic components, industrial equipment, technology and communication, cars and automobiles, chemical products and substances, general merchandise, beverages, personal care, and automated systems. To mention a few, we provide market-verified industry estimations, technical trend analysis, crucial market research, strategic advice, competition analysis, production and demand analysis, and client impact studies.

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Article originally posted on InfoQ. Visit InfoQ

Recently AWS announced the general availability (GA) of AWS AppFabric. This no-code service enhances companies’ existing investment in Software-as-a-Service (SaaS) applications with improved security, management, and productivity.

With AppFabric, users can easily integrate leading SaaS applications like Asana, Okta, Slack, and others supported without building and managing custom code or point-to-point integrations. Once connected, AppFabric ingests the data and normalizes disparate security data, such as user activity logs – accomplished through the company’s co-founded industry-standard schema and open-source project Open Cybersecurity Schema Framework (OCSF).

Enriching the data with a user identifier like a corporate email address reduces security incident response time as complete user information is available for each incident. The normalized and enriched data can be seamlessly integrated into preferred security tools like Logz.io, Netskope, Rapid7, Splunk, and others, enabling the establishment of consistent policies, streamlined security alerts, and simplified user access management across various applications.

Source: https://docs.aws.amazon.com/appfabric/latest/adminguide/what-is-appfabric.html

Users can access AWS AppFabric through AWS Management Console, AWS Command Line Interface (AWS CLI), and programmatically through the AppFabric API.

AWS AppFabric aims to address the challenges of integrating and managing multiple SaaS applications within organizations, which vice president of applications at AWS Dilip Kumar states in an AWS press release:

With AppFabric, customers now have a simple solution to deploy and scale the world’s most widely used applications in a way that helps organizations cut costs, increase productivity, and improve security.

In the future release of AWS AppFabric, users can benefit from additional generative artificial intelligence capabilities powered by Amazon Bedrock. This service makes popular foundational models available and customizable through an API.

AWS AppFabric is currently available in the US East (N. Virginia), Europe (Ireland), and Asia Pacific (Tokyo) regions, with availability in additional AWS Regions coming soon. Its pricing details are available on the pricing page.

Regarding pricing Randall Hunt, a VP of cloud at @CaylentInc, tweeted:

Played around with AWS AppFabric today. It works fine. However, I think AWS missed an opportunity to disrupt pricing on tools like this. Per-user pricing puts AWS competing with everyone else in the same space. $3/user/month is good pricing but not “I’m going to switch” pricing. What if they’d done it the same way as Amazon Connect and just completely disrupted the pricing for the industry? This service costs nothing but R&D to run, yet it can drive the adoption of 10s of other services.

Lastly, more details on AWS AppFabric are available in the documentation pages and FAQs.

Article originally posted on InfoQ. Visit InfoQ

As a person with autism or other neurodiversity, it’s important to get to know yourself really well. When possible, it’s even better if another person in your environment can get to know you from the inside-out. Dennie Declercq and his mom Ivette Marchand found a way to allow for open and vulnerable communication between them. This helped them make Declercq’s own life-manual, which enables him to be happy and productive as a software developer.

Dennie Declercq and Ivette Marchand gave a talk about autism coaching titled “How do I Help my Son, REVISITED” at NDC Oslo 2023.

After being diagnosed with autism, Declercq went to a school for adolescents with autism. The school specialised in autism, but he wasn’t allowed to study what he wanted. This resulted in a job he didn’t want. Declercq mentioned having loads of problems; he even was bullied by other adults. He was being pushed in the wrong box and couldn’t really develop a great life.

In 2011, Declercq had an emotional/mental crash and received a sickness benefit for a longer period of time. Due to that, he immediately went from a full-time job to being jobless.

After a while on sickness benefit, Declercq had the opportunity to leave the paid-work circuit and was offered a job as a software developer in a daycare centre for people with disabilities.

This was a job on a voluntary basis, which meant they couldn’t pay him, but he kept his fee from the government. His living costs are covered by this benefit. He doesn’t need to work, but he is allowed to spend free time working as a volunteer:  

This is really awesome, because you choose the job because you are really motivated to make a change. I could develop software for a good cause: people with learning disabilities. I could specialise myself and pay my living (bills, food, rent..) costs. This was the big turning point in my life. My environment changed to my needs and I started to get happy and productive.

Marchand mentioned that although they didn’t have the terminology, they started very early with making their own manual of understanding Declercq’s needs and the direct link to his behaviour. This also resulted in people who didn’t agree with their way of raising a child. But after all, they didn’t have a choice, Marchand mentioned.

A life manual is a continuous work-in-progress, from the time you start to craft your own manual until the end of your life. They made a life manual for everything in their life, not only for working. They don’t have everything written down, the reason being that as they have done this for such a long time, it has become a way of life. If you start making your own life-manual they advise you to document everything, writing down on oldschool paper or typing in a digital document.

Declercq and Marchand explained their methodology of autism-coaching.

It’s a combination of open and vulnerable communication and daring to share the details and making Declercq’s own life-manual. Of course, if you are making a life-manual for a life-time, you will need to remove parts, add parts and change your thoughts. This is not always easy and nice to do.

It’s like making a software methodology, trial and error. Sometimes there’s a bug in the way that Declercq handles a situation and debugging takes time. The good thing is, after a long debugging period, mostly we are blown away by the impact of the solution, Declercq mentioned.

Autism-coaching is not an official therapy but coaching is an official methodology in the field of working with people with disabilities. We are surrounded by people using this methodology, Declercq said.

Declercq’s biggest advice is to get to know yourself from the inside out. Learn about your problem triggers and energy givers. Make your own manual by documenting what gives energy and what takes it away.

If you don’t have your (dream) job yet, just believe in yourself, Declercq said. Believe you deserve to contribute to society with your programming super powers, but most importantly do know and believe society deserves your superpowers.

InfoQ interviewed Dennie Declercq and Ivette Marchand about living with autism and autism-coaching.

InfoQ: What did your life look before you were diagnosed with autism?

Dennie Declercq: My behaviour was not like the other children’s. It was not clear what I could say to whom. For example: I communicated in the same way to the head of my primary school as I talked to other children. Other people’s limits and boundaries were not clear to me, and I was over-communicating. As a result, a lot of people and other children didn’t like me. Children started to bully me and adults started to nag at me or my parents about my behaviour. This resulted in more problems.

Note that I can only talk about being a child if I talk about my life before I was diagnosed with autism; this is because my diagnosis was when I was 13 years old.

InfoQ: What happened after your autism diagnosis?

Declercq: The diagnosis didn’t fix my problems as a person with autism because my environment wasn’t able or willing to adapt to my needs. I was not allowed to study what I wanted. I kept being pushed in the wrong box and couldn’t really develop a great life.

For example, I was continuously pushed to do a job in a factory for people with disabilities, and I became mentally ill due to that job. If I cannot work with my brain, but have to do easy manual tasks, then my brain takes me to places where it’s not good for me!

Ivette Marchand: I was relieved knowing what was different about Dennie. We couldn’t understand Dennie’s behaviour- sometimes we thought he just behaved with bad intent.

At the same time that Dennie got his autism diagnosis, the clinic also advised us to take Dennie to a school for adolescents on the autism spectrum.

However, we didn’t agree that this school’s approach was completely right. I think the reality lied somewhere in the middle: understanding Dennie’s needs and behaviour was necessary, however following real strict planning and a balanced rest-and-activity system was not working either.

Declercq & Marchand: Let’s explain some pillars of our approach to making a life manual for yourself. Making a life manual is a huge topic, and this is just an article, so we will need to focus on just one example of the life manual; we will not be able to share the complete process to make a complete life-manual.

Let’s focus on energy, planning and communication in work situations.

• Each activity gives or takes energy:  start writing down what you did during the day and what the activity did to you. Were you more energetic after the activity, or were you more tired after the activity? Can you give it points on a scale?
• After a while you have a document with which activities give and take energy.
• If you know what gives and takes energy, try to plan your week accordingly so that there’s a balance between activities that give energy and activities that take energy.
• Communicate with trusted people around you about your feelings, when you feel energetic and tired. Communicate about your needs. Ask for help with activities that take too much energy.

An example of activities that give and take energy: some people get energy from doing coding work in an office on their own, while other people need people around them. For some people, meetings take up a lot of energy if they need to listen and take notes. Others love to brainstorm about new ideas.

InfoQ: How does having autism impact working life?

Declercq: This is a difficult question. I would say it has a big impact on my situation. For me, my autism resulted in not finding my way on the paid working circuit; rather I had a fee from the government and was only working as a volunteer at a daycare/ coaching centre for people with learning disabilities, where I developed software for people with disabilities, but not in my favourite technologies (.NET). After a while I got more self confident and founded DDSoft, a nonprofit initially making software for people with disabilities in .NET but later transitioned to a business connecting the social industry with the IT-industry. To make this concrete, I give an example for both: we give in-house training at (tech) companies about autism and accessibility, and we make IT-projects for social businesses (coaches, projects for people with disabilities).

Although it’s extremely important to say that this is my specific situation, it’s a combination of my autism, my childhood trauma and the school in that time not providing a curriculum for a job I really wanted and was all about my talents (being a software developer). Those three accumulated and made a job impossible for me. I do also know of some very talented people who have autism, and have been successful with paid work.

Marchand: Due to how our generation has grown up, as a starting point it was very important that Dennie had a job, even if it was not as a software developer but in a workplace for people with disabilities. We motivated Dennie a lot (rather, forced) to hold on to his job. Being without a job for a reason that “isn’t visible” was not done.

But, after seeing Dennie’s happiness and even mental and physical health going down very quickly, due to his having a job where he didn’t need to use his brains, we accepted that Dennie be jobless for a period. .

The first moment Dennie told us: “Maybe I can do volunteer work”, we shivered! But seeing how Dennie was finally rising and shining was the most important thing. We saw how he accelerated his own unique career. We heard about projects in the daycare/ coaching centre Dennie did, and how proud and confident he became. When Dennie took the first steps for his nonprofit, we saw how conscious and carefully he researched the steps to take without taking risks. And of course, we see how many conferences all over the globe invite Dennie to give presentations, and most importantly, how much energy those trips give to Dennie when he comes home. We are proud and happy!

In 2018 I had the privilege of being invited to join Dennie on his trip to NDC Oslo where Dennie gave a talk. Seeing and experiencing how Dennie lives and is really accepted at conferences made the circle complete!

InfoQ: How would you define autism-coaching?

Marchand: At first, it’s not always simple. It’s about having loads of patience and respect from both sides. It’s having close, honest and deep conversations. Sometimes it’s getting the best possible or least worst outcome.

Declercq: It’s having deep conversations and having a learning mindset. It’s learning about my own needs, my body and mind. Even though we have been doing this for years, sometimes I am still surprised by how big the difference is between what we think I need and what I really need.

For example: before the pandemic, my parents thought that I was doing too much out of home activities like conferences and business meetings in my own country (Belgium). But during the pandemic my parents saw how difficult my life was again due to too few stimuli. I knew that if you submit for conferences you receive rejections too, and you can’t decline an accepted talk because you had another conference last week (or in the same week). So I was submitting for a lot of conferences (and I still do).

Also for the nonprofit, I need to have a lot of events in my country to find my customers, and these can happen just a couple of days after a conference trip. My parents used to prevent me from doing too much and advised skipping meetings in my own country, for example. If I tried this, I didn’t find enough customers and our budget was running low. The other side is of course also true: sometimes I am very tired and stressed from having too much on my agenda.

InfoQ: What have you learned during the Covid-19 pandemic?

Declercq: That the world is not built for people who are different, and don’t fit in the box of “normally accepted”. With this I do talk about people who have different needs, opinions, struggles and thoughts, than the majority of people.

Next to this, people are blind to their own conditioning, generation after generation. For example, before the pandemic, even my parents thought that I travelled too much to speak at conferences, that this wasn’t necessary. During the pandemic, we saw that I really needed those trips. External stimuli from travelling (conferences, hotels, train stations, airports,…) do silence the internal stimuli in my head and body (dark thoughts, tense muscles, physical pains, …).

Most people advise a stimuli-less or stimuli-free way of living for people with autism. To be honest, this works for the majority of people with autism. The reason is that the majority of people with autism are introverted (90+%), whereas I am extroverted. Believe me, people have a big blind spot. This is not good.

Marchand: The media and governments did a “good job” in separating people, boxing and framing the “normally accepted way of living in times of pandemic”. Some examples they stigmatised:

• People who needed to see their parents, they ignored the need;
• People who did meet their friends when it was not allowed in during lockdown;
• People not being able to show proof of vaccination (multiple reasons: ex. not having a modern smartphone with the digital certificate, not being vaccinated for whatever reason, …)

The media, experts and politicians judged those people and separated them from the people “behaving as they should”. It’s really not ok to make such strict rules during lockdowns and in the process decline a lot of people’s mental health!

InfoQ: What’s your advice for developers who have autism? And for people working with them?

Declercq: Look for a person to help you if needed. Make a plan to communicate your needs to your closest bosses and co-workers. Decide if you need help from an autism or communication expert to structure the manual to pass to your team.

Marchand: Communicate a lot, have a lot of patience tunderstand how your autistic coworker works, and work together to the same goal. This approach provides an autism-friendly working environment, and you will be surprised by your coworkers’ abilities!

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Large Language Models have shown immense growth and advancements in recent times. The field of Artificial Intelligence is booming with every new release of these models. From education and finance to healthcare and media, LLMs are contributing to almost every domain. Famous LLMs like GPT, BERT, PaLM, and LLaMa are revolutionizing the AI industry by imitating humans. The well-known chatbot called ChatGPT, based on GPT architecture and developed by OpenAI, imitates humans by generating accurate and creative content, answering questions, summarizing massive textual paragraphs, and language translation. 

What are Vector Databases?

A new and unique type of database that is gaining immense popularity in the fields of AI and Machine Learning is the vector database. Different from conventional relational databases, which were initially intended to store tabular data in rows and columns, and more recent NoSQL databases like MongoDB, which store data in JSON documents, vector databases are different in nature. This is because vector embeddings are the only sort of data that a vector database is intended to store and retrieve.

Large Language Models and all the new applications depend on vector embedding and vector databases. These databases are specialized databases made for the effective storage and manipulation of vector data. Vector data, which uses points, lines, and polygons to describe objects in space, is frequently used in a variety of industries, including computer graphics, Machine Learning, and Geographic Information Systems. 

A vector database is based on vector embedding, which is a sort of data encoding carrying semantic information that aids AI systems in interpreting the data and in maintaining long-term memory. These embeddings are the condensed versions of the training data that are produced as part of the ML process. They serve as a filter used to run new data during the inference phase of machine learning. 

In vector databases, the geometric qualities of the data are used to organize and store it. Each item is identified by its coordinates in space and other properties that give its characteristics. A vector database, for instance, could be used to record details on towns, highways, rivers, and other geographic features in a GIS application.

Advantages of vector databases

1. Spatial Indexing – Vector databases use spatial indexing techniques like R-trees and Quad-trees to enable data retrieval based on geographical relationships, such as proximity and confinement, which makes vector databases better than other databases.

2. Multi-dimensional Indexing: Vector databases can support indexing on additional vector data qualities in addition to spatial indexing, allowing for effective searching and filtering based on non-spatial attributes.

3. Geometric Operations: For geometric operations like intersection, buffering, and distance computations, vector databases frequently have built-in support, which is important for tasks like spatial analysis, routing, and map visualization.

4. Integration with Geographic Information Systems (GIS): To efficiently handle and analyze spatial data, vector databases are frequently used in conjunction with GIS software and tools.

Best Vector Databases for Building LLMs

In the case of Large Language Models, a vector database is getting popular, with its main application being the storage of vector embeddings that result from the training of the LLM. 

1. Pinecone – Pinecone is a strong vector database that stands out for its outstanding performance, scalability, and ability to handle complicated data. It is perfect for applications that demand instant access to vectors and real-time updates because it is built to excel at quick and efficient data retrieval.

2. DataStax – AstraDB, a vector database from DataStax, is available to speed up application development. AstraDB streamlines and expedites the construction of apps by integrating with Cassandra operations and working with AppCloudDB. It streamlines the development process by eliminating the necessity for laborious setup updates and allows developers to scale applications automatically across various cloud infrastructures.

3. MongoDB – MongoDB’s Atlas Vector Search feature is a significant advancement in the integration of generative AI and semantic search into applications. With the incorporation of vector search capabilities, MongoDB enables developers to work with data analysis, recommendation systems, and Natural Language Processing. Atlas Vector Search empowers developers to perform searches on unstructured data effortlessly, which provides the ability to generate vector embeddings using preferred machine learning models like OpenAI or Hugging Face and store them directly in MongoDB Atlas.

4. Vespa – Vespa.ai is a potent vector database with real-time analytics capabilities and speedy query returns, making it a useful tool for businesses that need to handle data quickly and effectively. Its high data availability and fault tolerance are two of its primary advantages. 

5. Milvus – A vector database system called Milvus was created primarily to manage complex data in an effective manner. It provides fast data retrieval and analysis, making it a great solution for applications that call for real-time processing and instant insights. The capacity of Milvus to successfully handle large datasets is one of its main advantages.

In conclusion, Vector databases provide powerful capabilities for managing and analyzing vector data, making them essential tools in various industries and applications involving spatial information.

Don’t forget to join our 25k+ ML SubReddit, Discord Channel, and Email Newsletter, where we share the latest AI research news, cool AI projects, and more. If you have any questions regarding the above article or if we missed anything, feel free to email us at Asif@marktechpost.com

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References 

1. https://medium.com/gft-engineering/vector-databases-large-language-models-and-case-based-reasoning-cfa133ad9244
2. https://analyticsindiamag.com/10-best-vector-database-for-building-llms/
3. https://www.kdnuggets.com/2023/06/vector-databases-important-llms.html
4. https://www.datanami.com/2023/03/27/vector-databases-emerge-to-fill-critical-role-in-ai/

Tanya Malhotra is a final year undergrad from the University of Petroleum & Energy Studies, Dehradun, pursuing BTech in Computer Science Engineering with a specialization in Artificial Intelligence and Machine Learning.
She is a Data Science enthusiast with good analytical and critical thinking, along with an ardent interest in acquiring new skills, leading groups, and managing work in an organized manner.

Article originally posted on mongodb google news. Visit mongodb google news

Posted on nosqlgooglealerts. Visit nosqlgooglealerts

Report Ocean, a leading market research firm based in New York, USA, has recently unveiled a comprehensive research report titled “NoSQL Market” This report provides a meticulous analysis of competitors and key business segments from 2023 to 2031. It encompasses a thorough study of various segments, including opportunities, size, development, innovation, sales, and overall growth of major players. The research is based on a combination of primary and secondary statistical sources, incorporating both qualitative and quantitative analysis.

The global nosql market is projected to grow at a compound annual growth rate (CAGR) of 28.44% during the forecast period 2021-2027, according to the new report published by Report Ocean.

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The market research report covers the analysis of key stake holders of the nosql market. Some of the leading players profiled in the report include Aerospike, Amazon Web Services, Inc., Couchbase, Datastax, Google LLC, Marklogic Corporation, Microsoft Corporation, Mongodb Inc., among others.

The key objectives of this study are as follows:

• To conduct a comprehensive analysis of the market structure and provide forecasts for various segments and sub-segments of the global market.
• To provide insights into the factors influencing market growth and analyze the market based on factors such as price analysis, supply chain analysis, and Porter’s Five Forces analysis.
• To present historical and forecasted revenue figures for market segments and sub-segments in major geographies, including North America, Europe, Asia, Latin America, and the Rest of the World.
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The nosql market is segmented on the basis of type, application, end user, and region. The nosql market is segmented as below:

By Type:

column based stores
document databases
graph database
key-value store
By Application:
data analytics
data storage
mobile apps
web apps
others
By End User:
gaming
IT
retail
others
By Region:
region
Asia-Pacific
Europe
North America
Middle East and Africa (MEA)
South America

Scope of the Report
To analyze and forecast the market size of the global nosql market.
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To conduct pricing analysis for the global nosql market.
To identify and analyze the profile of leading players operating in the global nosql market.

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Key aspects covered in the report include:

• Exploration of new strategies and initiatives that market players can consider.
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• Detailed information on the forces shaping investment trends during the pandemic.
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We are the best market research reports provider in the industry. Report Ocean is the world’s leading research company, known for its informative research reports. We are committed to providing our clients with both quantitative and qualitative research results. As a part of our global network and comprehensive industry coverage, we offer in-depth knowledge, allowing informed and strategic business conclusions to report. We utilize the most recent technology and analysis tools along with our own unique research models and years of expertise, which assist us to create necessary details and facts that exceed expectations.

Get in Touch with Us:
Report Ocean:
Address: 500 N Michigan Ave, Suite 600, Chicago, Illinois 60611 – UNITED STATES
Tel:+1888 212 3539 (US – TOLL FREE)
Email: sales@reportocean.com
Visit our news Website: https://reportocean.com

Posted on mongodb google news. Visit mongodb google news

Dow Jones futures were lower on Tuesday and the stock market was closed for the July 4 holiday. Major stock indices ended right at their 2023 highs on Monday, as Tesla shares soared to new highs with record second-quarter deliveries. Meanwhile, a crucial jobs report for June looms on Friday.

X

On Monday, the Dow Jones Industrial Average rose slightly higher, while the S&P 500 gained 0.1%. The technology exchange Nasdaq rose 0.2%.

On the economic front, this week’s Friday Labor Department jobs report is in the spotlight. Economists predict a gain of about 200,000 jobs and a fall in the unemployment rate to 3.6%.

Ahead of that crucial jobs report, the minutes of the Fed’s June 13-14 meeting will be out at 2 p.m. Wednesday. They could shed light on why policymakers’ forecasts came in for two more rate hikes.

Thursday will bring a good dose of data. Payroll processor ADP releases its estimate of private sector job growth for June at 8:15 a.m. The first unemployment claims must be submitted by 8:30 am. Both reports are seen as precursors to the monthly salary report. The ISM Service Index is released at 10 a.m. along with the Labor Department’s monthly job and labor turnover survey.

Fair today

EV giant Tesla (TSLA) rose nearly 7% after the company reported record second-quarter deliveries that beat estimates. Dow Jones tech giants Apple (AAPL) and Microsoft (MSFT) fell 0.8% and 0.75% respectively in the current stock market action.

Chipotle Mexican Grill (CMG), Dynatrace (DT), MongoDB (MDB), Lamb research (LRCX) and Nvidia (NVDA) — as well as Dow Jones stock JPMorgan Chase (J.P.M.), Visa (V) and Sales team (CRM) – are among the best stocks to watch in the continued progress in the stock market.

Tesla is an IBD Leaderboard stock, Lam Research remains an IBD SwingTrader stock, while Nvidia was seen in the stock column this week near a buy zone. Dynatrace was a recent IBD Stock Of The Day.

IBD’s latest newsletter MarketDiem gives you actionable ideas for stocks, options and cryptocurrencies straight to your inbox

Dow Jones Today: Oil Prices, Treasury Yields

The exchange is closed on Tuesday, with limited futures trading.

Ahead of Wednesday’s opening bell, Dow Jones futures were down 0.15% from fair value, while S&P 500 futures were slightly lower. Nasdaq 100 futures were barely below fair value. Remember that overnight action in Dow futures and elsewhere does not necessarily translate into actual trading in the next regular trading session.

On Monday, the 10-year US Treasury yield ticked higher to 3.85%. Oil prices rose 1.5% on Tuesday after their recent lows. West Texas Intermediate futures traded at around $71 a barrel.

Stock market action: what to do now

Now is an important time to read IBD’s The Big Picture column with major stock indices at their 2023 highs.

As the stock market is at its peak this year, IBD’s recommended exposure level is 80% to 100%. However, investors should be careful when adding exposure, taking stock of current market levels and increasing at a measured pace. It’s also important to stay nimble in case another pullback comes along.

Five best Dow Jones stocks to buy and watch right now

Dow Jones stocks to watch: JPMorgan, Salesforce, Visa

Dow Jones bank leader JPMorgan rose further above a 143.37 flat-base buy point during Monday’s earnings. The 5% buy zone goes up to 150.54.

Salesforce managed to stabilize itself after a post-revenue pullback. It is now testing support on the 50-day line. A decisive bounce would provide a new item.

According to the IBD Leaderboard analysis, the megacap technology previously passed a pair of alternate entries at 194.01 and at 200.10. In recent weeks, shares hit the 20% gain zone from a 178.94 cup entry with handle.

Payments leader Visa surpassed the buy point of a flat base of 235.57 last week and added to that gain on Monday, rising 0.2%. The buy range comes out at 247.35.

4 Top growth stocks to watch Stock market rally

Best stocks to buy and watch: Chipotle, Dynatrace, MongoDB, Lam Research, Nvidia

IBD Leaderboard watchlist stock Chipotle is trying to break out past the 2,139.88 buying point from a flat base, according to IBD MarketSmith pattern recognition. An early entry at 2,092.51 was also available due to a trendline. Chipotle was a recent IBD stock of the day.

Software maker Dynatrace has formed a three-week chart pattern, representing a brief consolidation in which institutional investors pause their purchases. Shares are about 3% off their last entry at 52.99.

IBD SwingTrader share Lam Research rose above a 615.80 early buy point and a three week tight pattern with a 630.72 entry during last week’s gains. Shares stuck at 1.3% Monday.

MongoDB traded briskly after its recent profit-driven jump, which offered another entry. Shares are above the three-week tight formation that showed a buy point at 398.89, while aggressive investors could have used a trendline entry around 386.

After the May 25 earnings-fueled gap-up, Nvidia shares have moved consistently higher. Amid a pullback since June 20, the stock is once again offering an opportunity to buy shares. It formed a trendline entry at 418 after the stock found support near its 21-day exponential moving average. Nvidia is an IBD Leaderboard stock.

Learn how to time the market with IBD’s ETF market strategy

Best stocks to buy and watch in stock market rally

Here are the top four stocks to buy and watch in the current stock market, including a Dow Jones leader.

Source: IBD data as of July 3, 2023

Join IBD experts as they analyze leading stocks in the current stock market rally on IBD Live

Tesla stock

IBD Leaderboard share Tesla extended a profit stretch to five sessions on Monday. Amid the recent upswing, Tesla shares remain well out of the buy range past the double bottom buy point of 207.79.

TSLA stock rose 6.9% on Monday after the company said it delivered more than 466,000 vehicles to customers around the world in the April-June period, a record quarter for sales. Price reductions and discounts drove demand well above Wall Street forecasts.

Dow Jones leaders: Apple, Microsoft

Among Dow Jones stocks, Apple stock faded from Friday’s all-time high of 194.48, falling 0.8% on Monday. Shares remain sharply above a buy point of 157.38.

Microsoft shares lost 0.75% on Monday, returning some of Friday’s gains. Still, the stock is just 4% off its all-time high on June 16 at 351.47.

In recent weeks, the stock hit the 20% to 25% gain zone from a 276.76 flat-base buy point, so investors could have at least taken some profit there.

Follow Scott Lehtonen on Twitter at @IBD_SLehtonen for more information on growth stocks and the Dow Jones Industrial Average.

YOU MAY ALSO LIKE:

Top growth stocks to buy and watch

Learn how to time the market with IBD’s ETF market strategy

Find the best long-term investments with long-term IBD leaders

MarketSmith: research, charts, data and coaching all in one place

How To Research Growth Stocks: Why This IBD Tool Simplifies Searching For Top Stocks

Article originally posted on mongodb google news. Visit mongodb google news

Article originally posted on InfoQ. Visit InfoQ

Researchers from UC Berkeley and Microsoft Research have open-sourced Gorilla, a large language model (LLM) that can write code to call APIs. In experiments measuring generated code accuracy, Gorilla outperforms several baseline models, including GPT-4.

Described as “an API appstore for LLMs,” Gorilla is based on the LLaMA open-source LLM. The LLM is finetuned on APIBench, a new dataset of API descriptions of ML models hosted on HuggingFace, TorchHub, and TensorHub. Gorilla can also call out to an external document database of API definitions, which allows it access to new APIs without re-training. Using Gorilla, developers can create natural language descriptions of a problem, such as “Invoke an image classification model that uses less than 10M parameters, but maintains an ImageNet accuracy of at least 70%.” Gorilla would then output the Python code to invoke the appropriate ML model with the proper options. According to the authors, 

LLMs are swiftly gaining popularity across diverse domains. In our study, we spotlight techniques designed to enhance the LLM’s ability to accurately identify the appropriate API for a specific task—a significant but often overlooked aspect in the advancement of this technology. Since APIs function as a universal language enabling diverse systems to communicate effectively, their correct usage can boost the ability of LLMs to interact with tools in the wider world.

LLMs like GPT-4 have excellent performance on a wide range of tasks, including generating code. However, their knowledge of APIs is “frozen” at training time, so that they cannot generate code to call newer APIs. Further, they often hallucinate—in the case of code generation, they might output a call to an API that does not exist. InfoQ has covered several recent efforts to address these issues; for example, Meta’s Toolformer which can invoke external service APIS, and ChatGPT’s plugin system that augments the LLM with external resources.

The Berkeley team points out, however, that these approaches are based on prompting the LLM with examples of API calls. By contrast, the Gorilla approach focuses on “systematic evaluation and building a pipeline for future use.” The researchers began by assembling the APIBench dataset. The team first collected all the model cards from the HuggingFace model hub, PyTorch hub, and TensorFlow hub. After filtering, this produced a collection of 1,645 API calls. For each of those, the researchers used GPT-4 to generate a dataset of instruction-api pairs for fine-tuning Gorilla.

A major challenge in evaluating Gorilla’s output was to identify hallucinations. First, the team defined a hallucination as any model output that calls an API not in the model’s external database of API definitions. This is contrasted with an error, which is an output that simply calls a “real” API incorrectly. The team used the abstract syntax tree (AST) of the generated code to match with APIs in the database and test set for evaluation purposes. Using this AST accuracy metric on zero-shot tasks, Gorilla performed 20.43% better than GPT-4.

Gorilla’s lead author Shishir Patil joined a Hacker News discussion about the work, answering several questions. When asked whether the model’s license allowed commercial use, Patil pointed out that there are three versions of Gorilla. The one based on LLaMA is not licensed for commercial use, but the ones based on MPT-7 base and Falcon-7B are. Another user asked how Gorilla compared to LangChain; Patil replied:

Langchain is a terrific project that tries to teach agents how to use tools using prompting. Our take on this is that prompting is not scalable if you want to pick between 1000s of APIs. So Gorilla is a LLM that can pick and write the semantically and syntactically correct API for you to call! A drop in replacement into Langchain!

The Gorilla code and model files are available on GitHub. There is also a Google Colab notebook demo of the model.

Article originally posted on InfoQ. Visit InfoQ

Time plays a critical role in software applications. Tracking time zones and testing time-dependent flows bring challenges to developers. The first part of the article covers the history of .NET Date and Time structures, including existing issues and challenges in time calculation. The second part reviews new .NET 8 Preview 4 abstractions that improve dependency injection and unit testing.

Challenges in utilizing old date and time structures in .NET

DateTime

DateTime has been the main structure for storing date and time in .NET since version 1.1. It has a major drawback – a lack of a time zone. To overcome this problem, the Kind property was added with three possible values: Local, Utc, or Unspecified.

By default, DateTime.Now initializes the local time instance with the Kind property equal to Local.

       var now = DateTime.Now;
       Console.WriteLine("Now: {0}", now);
       Console.WriteLine("Kind: {0}", now.Kind);

Output:

Now: 06/15/2023 11:00:00
Kind: Local

For the conversion to UTC, it is possible to call the DateTime.Now.ToUniversalTime() method, or simply use the DateTime.UtcNow property.

       var now = DateTime.Now;
       var utc1 = now.ToUniversalTime();
       Console.WriteLine("UTC 1: {0}",utc1);
       Console.WriteLine("UTC 1 Kind: {0}", utc1.Kind);
		
       var utc2 = DateTime.UtcNow;
       Console.WriteLine("UTC 2: {0}", utc2);
       Console.WriteLine("UTC 2 Kind: {0}", utc2.Kind);

Output:

UTC 1: 06/15/2023 11:00:00
UTC 1 Kind: Utc
UTC 2: 06/15/2023 11:00:00
UTC 2 Kind: Utc

How does .NET understand the time zone difference during translation from local time to UTC if DateTime does not provide this information?

The ToUniversalTime method takes the time zone from the operating system, an approach that might be problematic. Let’s consider a local DateTime.Now instance that is created in a New York server and then transferred to a London server.

After the conversion to UTC simultaneously on both servers, the results will be different:

      var nowInNewYork = DateTime.Now;
	  var utcInNewYork = nowInNewYork.ToUniversalTime();		
	  Console.WriteLine("UTC in New York: {0}", utcInNewYork);

      // Send locally initiated nowInNewYork to a London server
	  var utcInLondon = nowInNewYork.ToUniversalTime();		
      Console.WriteLine("UTC in London:   {0}", utcInLondon);

Output:

UTC in New York: 06/15/2023 11:00:00
UTC in London:   06/15/2023 07:00:00

This approach led to confusion and frustration for developers; the problems were described in the Microsoft blog along with endless Stackoverflow questions.

On this occasion, Microsoft released the Coding Best Practices Using DateTime in the .NET Framework, shifting all responsibility to the developers:

A developer is responsible for keeping track of time-zone information associated with a DateTime value via some external mechanism. Typically this is accomplished by defining another field or variable that you use to record time-zone information when you store a DateTime value type.

.NET expects time-zone information to be paired with the Kind property during date and time restoration: DateTimeKind.Local with TimeZoneInfo.Local, DateTimeKind.Utc with TimeZoneInfo.Utc, and DateTimeKind.Unspecified for anything else. Custom time zone, as Microsoft recommends, requires to use DateTimeKind.Unspecified:

       var nowInNewYork = DateTime.Now;   
	   Console.WriteLine("New York local time: {0}", nowInNewYork);

      var newYorkTimeZone =
 TimeZoneInfo.FindSystemTimeZoneById("Eastern Standard Time");
	  nowInNewYork = DateTime.SpecifyKind(nowInNewYork, DateTimeKind.Unspecified);

       // Now on any server, in New York or London, UTC is correct
       var utc = TimeZoneInfo.ConvertTimeToUtc(nowInNewYork, newYorkTimeZone)
	   Console.WriteLine("UTC: {0}", utc);

Output:

New York local time: 06/15/2023 12:00:00
UTC: 06/15/2023 16:00:00

An alternative solution may be to create and store time only in the UTC format:

var dtInUtc = DateTime.UtcNow;

then convert it every time to a local time on the user’s side:

var dtLocal = dtInUtc.ToLocalTime();
// or
var dtLocal = TimeZoneInfo.ConvertTimeToUtc(dtInUtc, clientTimeZone);

Unfortunately, this requires additional code checks against accidental use of DateTime with a local initialization via DateTime.Now, and also does not exclude such nuances as daylight saving rule changes. I will discuss it in the next section.

DateTimeOffset

As an improvement, the DateTimeOffset structure was introduced in .NET 2. It consists of:

• structure DateTime
• property Offset storing time difference relative to UTC.

The problem with servers in different time zones will not affect DateTimeOffset.Now – this is not a panacea for all cases.

Assume there is a need to save an April appointment with a doctor in London. The time zone for London in .NET is TimeZoneInfo.FindSystemTimeZoneById("GMT Standard Time"), passing it to DateTimeOffset will result in a correct instance, for example, equal to 2023-04-01 14:00:00 with Offset = +1. Due to daylight saving in Britain, Offset equals +1 at the end of March and equals 0 at the beginning of March. In some countries, there is no daylight saving time. For example, in Nigeria, Offset is always equal to +1.

The daylight saving rules are subject to change, with alternation happening almost every year. It will not be possible to determine the origin of date and time just by looking at the Offset value, whether it was created for Britain or Nigeria with the same value “01:00:00”:

 var dt = DateTimeOffset.Now; 
 Console.WriteLine(dt.Offset);

Output:

01:00:00

Thus, for international software, it is better to store the time zone for possible recalculation of Offset according to the new rules; TimeZoneInfo class suits this requirement.

Writing unit tests with time before .NET 8 Preview 4

For unit testing, it is important to be able to mock a method call on an object with a custom implementation. As DateTime and DateTimeOffset do not have interfaces, it is possible to create a custom abstraction and later mock them during tests. For example, the following interface can provide an abstraction for DateTimeOffset:

public interface ISystemClock
{
    DateTimeOffset UtcNow { get; }
}

A similar approach was used internally at Microsoft where the same code was added to at least four different areas in .NET.

What about alternative solutions?

Jon Skeet created the NodaTime library with the correct time processing of non-trivial cases, and of course, with the support of abstractions.

Alright, using some custom interface for your code base is possible. Though how can you create integration tests with external libraries that require time transfer via DateTime and DateTimeOffset types?

Microsoft has a tool called .NET Fakes that can generate mocks and stubs for any .NET library. For example, it is possible to overwrite all static calls of DateTime.Now in unit tests with

System.Fakes.ShimDateTime.NowGet = () => { return new 
DateTime(2025, 12, 31); };

It works, but there are limitations.

First, the generator is compatible only with Windows OS. Second, at the time of writing, it is included only in the Visual Studio Enterprise version, priced at $250 per month. Third, it is a complex and the most advanced integrated development environment tool from Microsoft. It takes a lot of resources and local storage space, compared to the lightweight Visual Studio Code IDE.

Writing unit tests with time in .NET 8 Preview 4

The long-awaited time abstractions were added after years of debates and hundreds of comments for .NET 8 RC: TimeProvider and ITimer.

public abstract class TimeProvider
{
    public static TimeProvider System { get; }
    protected TimeProvider()
    public virtual DateTimeOffset GetUtcNow()
    public DateTimeOffset GetLocalNow()
    public virtual TimeZoneInfo LocalTimeZone { get; }
    public virtual long TimestampFrequency { get; }
    public virtual long GetTimestamp()
    public TimeSpan GetElapsedTime(long startingTimestamp)
    public TimeSpan GetElapsedTime(long startingTimestamp, long endingTimestamp)
    public virtual ITimer CreateTimer(TimerCallback callback, object? state,TimeSpan dueTime, TimeSpan period)
}

public interface ITimer : IDisposable, IAsyncDisposable
{
    bool Change(TimeSpan dueTime, TimeSpan period);
}

Ultimately, it did not turn out to be flawless, but this represents significant progress.

TimeProvider disadvantages

1. The abstract class came out bulky. For a method that takes a TimeProvider argument, it is not possible to decide which method to mock without knowing internal details: GetUtcNow(), GetLocalNow(), CreateTimer(...), or all of them. Developers proposed to break the new type into small interfaces, in particular, similar to the one already used internally at Microsoft:

public interface ISystemClock
{
    public DateTimeOffset GetUtcNow();
}

public abstract class TimeProvider: ISystemClock {
    // ...
}

That idea had been rejected.

2. An instance of TimeProvider can be created with the help of a static TimeProvider.System call. It is very easy to use for a developer, though it is not so different from the old usage of static DateTime.Now. Later it will result in problems with unit test writing without a special FakeTimeProvider.
Instead of a direct static call, it is expected that developers will use Dependency Injection for TimeProvider. For example, code for ASP.NET Core can look like

public class MyService
{
    public readonly TimeProvider _timeProvider;

    public MyService(TimeProvider timeProvider){
        _timeProvider = timeProvider;
    }

    public boolean IsMonday() {
        return _timeProvider.GetLocalNow().DayOfWeek == DayOfWeek.Monday;   
    }         
}

// Dependency injection:
var builder = WebApplication.CreateBuilder();
builder.Services.AddSingleton(TimeProvider.System);
builder.Services.AddSingleton();

This can be non-trivial for beginner programmers.

TimeProvider and ITimer advantages

1. Time-dependent unit testing becomes more universal. TimeProvider was added to BCL to support a wide variety of .NET runtimes. It becomes possible to cover the above MyService example with a unit test:

using Moq;
using NUnit.Framework;

[Test]
public void MyTest()
{
    var mock = new Mock();
 mock.Setup(x => x.GetLocalNow()).Returns(new DateTimeOffset(2025, 12, 31, 23, 59, 59, TimeSpan.Zero));
    var mockedTimeProvider = mock.Object;

    var myService = new MyService(mockedTimeProvider);
    var result = myService.IsMonday(mockedTimeProvider);
    Assert.IsTrue(result, "Should be Monday");
}

2. The Microsoft team did not bring in the new implementation of the old error where properties had side effects. This is how DateTime.Now property was mistakenly introduced instead of the DateTime.Now() function. TimeProvider abstracts time side effects with functions and methods: GetUtcNow(), GetLocalNow(), GetTimestamp(), etc.

3. It is possible to test time series events with TimeProvider.CreateTimer(...) and Timer.Change(...) functions. This is especially important for Task.Delay(...) and Task.WaitAsync(...)function calls, which now also accept a TimeProvider argument.

4. There is a plan to create FakeTimeProvider as part of .NET to further simplify unit testing. Perhaps then the negative point 2 will not be relevant.

Stephen Toub, a software engineer at Microsoft, wrote:

At the end of the day, we expect almost no one will use anything other than TimeProvider.System in production usage. Unlike many abstractions then, this one is special: it exists purely for testability.

Conclusion

The introduction of the class TimeProvider in .NET 8 Preview 4 specifies a standardized and unified abstraction for managing time. While it may have a few minor drawbacks, Microsoft teams internally marked their custom time interfaces as obsolete and now advocate for adopting TimeProvider.

Posted on mongodb google news. Visit mongodb google news

It’s better to be a top company in a hot field than a leader in a struggling industry. So investors should look for the best stocks in the best groups. Super micro computer (SMCI), li car (LI), Duolingo (DUOL), MongoDB (MDB) and Allegro MicroSystems (ALGM) are the top-rated stocks in the five strongest industry groups so far this year.

X

SMCI stock is the No. 1 stock in the Computer-Hardware/Peripherals group, according to IBD Stock Checkup. that’s just over 95% through June 30. LI stocks, no Tesla (TSLA), is No. 1 in the Auto Manufacturers group, up 55.8% in 2023. DUOL stock tops the Computer Software-Education/Media group, which is up 54.5% this year increased. MDB stock leads the Computer Software-Database group, which is up 52.6% year-to-date. ALGM stock is No. 1 in Electronic-Semiconductor Faless which also includes Nvidia (NVDA). Fabless chipmakers are up 46.5% mid-year.

Top Industry Groups of 2023

Nvidia stock, Tesla and MongoDB are on IBD Leaderboard. Allegro MicroSystems and MDB stock are on the IBD 50. Tesla stock and MongoDB are on the IBD Big Cap 20

SMCI stock

Super Micro is the highest-rated stock in the computer hardware/peripherals group. And it’s not hard to see why. SMCI’s share will triple (203.6%) by 2023, including a 133.9% increase in the second quarter.

Earnings growth was tremendous, although it slowed to just 5% in the last quarter.

Super Micro shares broke out of a consolidation in February, though that would have been hard to sustain a few weeks later. SMCI shares then shot out of a messy six-week profit margin and continued to soar to a record high of 270.18 on June 9. to a Super Micro position.

Other top stocks in the group include Corsair gaming (CRSR), IonQ (IONQ), Dell Technologies (DELL) and logitech (LOGI).

Cathie Wood Stock is expected to deliver 772% EPS gains. It flashes a buy signal.

Li car stock

Li Auto is number 1 in the Automakers group. With EV sales booming, revenue and revenue growth is accelerating rapidly. LI shares are up 72.1% so far in 2023, including a 40.7% gain in the second quarter.

Equities tried to break out in late March and mid-April, but those moves immediately came to nothing. Finally, on May 10, Li Auto fell out of base on a hot earnings report. A few weeks later, LI stock offered another entry as it recovered from the 21-day line and cleared a brief consolidation.

Other top auto stocks include Ferrari (RACE), Ford engine (F), Tesla stock and Stellantis (STLA).

TSLA stock has skyrocketed 112.5% ​​in 2023, though Q2 earnings lagged Li Auto’s by 26.2%. Also, Tesla’s revenues fell year-on-year in the first quarter, while revenue growth slowed.

Duolingo stock

DUOL stock is No. 1 in the education/media software industry. The language learning platform doubled (101%) in 2013, but had risen only a fraction by 2023.

Duolingo is still losing money, but is expected to turn a profit later this year. Revenue growth is robust.

Duolingo shares rose at the start of 2023 and came out of a long consolidation in early March based on first-quarter numbers. Shares continued to run through March, then consolidated. DUOL shares plummeted in early May on AI fears, but then cleared that area based on Q2 earnings, as Duolingo touted how AI is a boon to its company. Shares reached a 52-week high of 168.40 on June 6. Duolingo stock subsequently retreated below the 50-day line, where it is currently experiencing resistance. A move above the 50-day and 21-day lines could offer early entry.

Duolingo uses AI to revolutionize learning, engage users and drive explosive growth

Other top stocks in Duolingo’s group include Coursera (COUR), Instruct (INST), Spotify (SPOT) and Udemy (UDMY).

MongoDB share

MDB stock is No. 1 in the Software Database group. MongoDB is up 108.8% in 2023, including a peak of 76.3% in the second quarter. Now consistently profitable, MongoDB has reported three consecutive quarters of triple-digit earnings growth.

MongoDB shares rose in January and then consolidated for three months before a breakout in early May. The shares then diverged in the fiscal Q1 earnings report. MDB stocks consolidated to form a three-week tight with elements of a high tight flag. Stocks just cleared that area, though MongoDB is still usable.

Other top database software manufacturers include Progress software (PRGS), Drop box (DBX), Splunk (SPLK) and Commvault Systems (CVLT).

Allegro Micro stock

Allegro Microsystems stock leads the semiconductor fabless group. Fabless chipmakers lack their own factories or “fabs.” They rent chip foundries like Taiwan semiconductor (TSM) to make their chips.

The ALGM share increased by 50.4% in 2023. Equities actually fell 5.9% in the second quarter, but rallied strongly in May and June. Allegro Micro’s earnings rose 76% in March’s fiscal fourth quarter, a three-quarter streak of accelerating earnings growth. Over the past five quarters, sales gains have accelerated.

Allegro Micro stock broke out in January, one of the early tech leaders in 2023. Shares rose to a record high of 48.72 on April 3, then sold hard and fell well below the 50-day mark. Stocks started bouncing in late April. On June 13, ALGM shares reclaimed the 50-day line. A few days later, ALGM broke a short-term high and broke a trendline, offering an early entry. Shares then paused amid the market’s pullback, but rallied again last week. Allegro now extends from that early entry, working its way up to 48.72 buys in a cup base, according to MarketSmith’s analysis.

Other top fabless chip stocks include Lattice semiconductor (LSCC), Rambus (RMBS), Monolithic energy systems (MPWR) and Nvidia stock.

AI plays 5 stocks near buy points

NVDA stock was the big-cap tech winner of 2023, rising 189.5% in 2023 and 52.3% in the second quarter. Nvidia now has a $1 trillion market cap. Stocks recovered from close to the 21-day line, breaking a brief downtrend, offering an aggressive entry.

Nvidia’s revenues have declined over the past four quarters, a major reason why NVDA stocks are not number 1 in their group. But investors expect Nvidia’s earnings per share to more than double in the current fiscal year, thanks to the company’s excellent guidance as the chipmaker leads the AI ​​boom.

Remember, investors should never buy based on ratings alone. They are a useful screening tool, but purchasing decisions should be made with an eye to the action on the chart, market conditions and much more.

Follow Ed Carson on Twitter at @IBD_ECarson for stock market updates and more.

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