Month: June 2023

Article originally posted on InfoQ. Visit InfoQ

The Angular Mini-Book is a guide to getting started with Angular. You’ll learn how to develop a bare-bones application, test it, and deploy it. Then you’ll move on to adding Bootstrap, Angular Material, continuous integration, and authentication.

Spring Boot is a popular framework for building REST APIs. You’ll learn how to integrate Angular with Spring Boot and use security best practices like HTTPS and a content security policy. What about deploying your Angular app to the cloud? Yep, it covers that too!

This third edition (v3.0) uses Angular 15 and Spring Boot 3.0.

You can download the code for this book’s examples here.

Follow @mraible on Twitter for book updates.

Purpose of the book

I think building web and mobile applications with Angular, Bootstrap, and Spring Boot is a great experience. I’d like to encourage more developers to try it.

Free download

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In a major announcement at its developer conference, MongoDB has launched the MongoDB AI Innovators Program. 

This groundbreaking initiative aims to expedite the adoption of generative AI technology by offering organizations access to MongoDB Atlas credits, partnership opportunities within the MongoDB Partner Ecosystem, and collaborative go-to-market activities.

With a focus on accelerating innovation and time to market, the program comprises two distinct tracks: AI Startups for early-stage ventures and AI Amplify for more established companies. By joining this program, participants gain exclusive access to a vibrant community of founders, developers, and MongoDB experts, creating an environment conducive to the rapid development of AI-powered solutions. To learn more and take part in the MongoDB AI Innovators Program, interested parties can visit mongodb.com/startups/ai-innovators.

The rise of generative AI is reshaping technology across various domains, transforming everything from developer tools to end-user experiences. In today’s fast-paced world of innovation, organizations of all sizes, including startups and established enterprises, are keen to harness the potential of generative AI.

They aspire to revolutionize their business operations, pioneer novel ways of conducting business, and disrupt entire industries. However, integrating generative AI into existing applications presents significant challenges. It often entails the need to bolt on additional technology or develop entirely new applications from scratch, both of which are time-consuming, expensive, and require specialized expertise.

Consequently, many organizations find it difficult to identify the optimal path forward, risking lagging behind their competitors. These organizations yearn for a clear roadmap to innovation in generative AI. They seek opportunities to collaborate with established technology leaders, access cutting-edge tooling, engage subject matter experts, and expedite the deployment of their AI-powered applications.

The MongoDB AI Innovators Program addresses these pressing needs, empowering organizations to overcome barriers and embrace generative AI with confidence. The program offers an array of benefits and collaborative initiatives designed to fuel success:

Expanded MongoDB Atlas credits

The AI Startup track of the MongoDB AI Innovators Program provides eligible organizations with up to $25,000 in credits for MongoDB Atlas. As the leading multi-cloud developer data platform, MongoDB Atlas offers unparalleled support for building data-driven applications. With advanced capabilities for working with large-language model (LLM) embeddings and seamless integration with LLM tools and providers like AWS, Google Cloud, and Microsoft Azure, organizations can harness the power of MongoDB Atlas to reimagine end-user experiences. Since 2019,

MongoDB has already provided over $25 million in credits to more than 8,000 startups, facilitating rapid application prototyping and production with MongoDB Atlas. With expanded access to credits, startups can overcome technological obstacles and transform their ideas into AI-powered solutions faster and at a reduced cost.

Startups entering the program through MongoDB Partners, including AWS, Google Cloud, and Microsoft Azure, also gain access to these expanded credits and can even explore collaboration opportunities with MongoDB Ventures for early-stage funding.

Amplified visibility and accelerated time to market

The AI Amplify track, open to organizations of various sizes and business models, offers a pathway to increased visibility and accelerated time to market. Submissions by participants in this track receive expedited evaluation by MongoDB experts and are considered for strategic partnerships and joint go-to-market initiatives. This track empowers companies to gain greater exposure for their projects and access new markets. MongoDB’s technical experts are readily available to provide solutions architecture support and assist in identifying compelling use cases for co-marketing opportunities.

Access to MongoDB Partners and solutions

The MongoDB Partner Ecosystem, consisting of over 1,000 organizations ranging from Databricks to BigID to Accenture, is a valuable resource for MongoDB customers. MongoDB has the distinction of being the only independent software vendor (ISV) featured in the startup programs of all three major cloud providers. Esteemed companies like Forbes, Toyota, and Powerledger have already leveraged MongoDB’s industry solutions and technology integrations through partnerships within this ecosystem.

By participating in the MongoDB AI Innovators Program, organizations gain prioritized access to MongoDB Partner opportunities. Eligible organizations can be fast-tracked to join the MongoDB Partner Ecosystem, enabling them to build seamless and interoperable integrations, collaborate on cutting-edge solutions, or showcase their expertise and certified skills in delivering AI-powered services. With a shared focus on go-to-market strategies, this collaboration between MongoDB and its partners facilitates the deployment of AI solutions to both existing and untapped user bases.

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

Posted on mongodb google news. Visit mongodb google news

Diversified Trust Co raised its holdings in MongoDB, Inc. (NASDAQ:MDB – Get Rating) by 132.0% in the 1st quarter, according to its most recent Form 13F filing with the Securities & Exchange Commission. The institutional investor owned 2,863 shares of the company’s stock after purchasing an additional 1,629 shares during the period. Diversified Trust Co’s holdings in MongoDB were worth $667,000 at the end of the most recent reporting period.

Other large investors have also recently modified their holdings of the company. Bessemer Group Inc. purchased a new position in MongoDB during the fourth quarter valued at approximately $29,000. BI Asset Management Fondsmaeglerselskab A S purchased a new position in MongoDB during the fourth quarter valued at approximately $30,000. Lindbrook Capital LLC grew its stake in MongoDB by 350.0% during the fourth quarter. Lindbrook Capital LLC now owns 171 shares of the company’s stock valued at $34,000 after acquiring an additional 133 shares in the last quarter. Y.D. More Investments Ltd purchased a new position in MongoDB during the fourth quarter valued at approximately $36,000. Finally, CI Investments Inc. grew its stake in MongoDB by 126.8% during the fourth quarter. CI Investments Inc. now owns 186 shares of the company’s stock valued at $37,000 after acquiring an additional 104 shares in the last quarter. Hedge funds and other institutional investors own 89.22% of the company’s stock.

Analyst Ratings Changes

Several equities analysts recently commented on MDB shares. KeyCorp boosted their price objective on shares of MongoDB from $229.00 to $264.00 and gave the company an “overweight” rating in a research note on Thursday, April 20th. Guggenheim lowered shares of MongoDB from a “neutral” rating to a “sell” rating and lifted their target price for the company from $205.00 to $210.00 in a research report on Thursday, May 25th. They noted that the move was a valuation call. Piper Sandler lifted their target price on shares of MongoDB from $270.00 to $400.00 in a research report on Friday, June 2nd. Credit Suisse Group dropped their target price on shares of MongoDB from $305.00 to $250.00 and set an “outperform” rating for the company in a research report on Friday, March 10th. Finally, JMP Securities lifted their target price on shares of MongoDB from $245.00 to $370.00 in a research report on Friday, June 2nd. One research analyst has rated the stock with a sell rating, two have given a hold rating and twenty-one have given a buy rating to the stock. Based on data from MarketBeat.com, the company currently has an average rating of “Moderate Buy” and a consensus target price of $328.35.

MongoDB Stock Up 4.1 %

Shares of NASDAQ MDB opened at $388.36 on Friday. The company has a quick ratio of 4.19, a current ratio of 4.19 and a debt-to-equity ratio of 1.44. MongoDB, Inc. has a 52 week low of $135.15 and a 52 week high of $398.89. The firm’s fifty day moving average is $292.30 and its 200 day moving average is $236.48. The company has a market cap of $27.20 billion, a price-to-earnings ratio of -83.16 and a beta of 1.04.

MongoDB (NASDAQ:MDB – Get Rating) last issued its earnings results on Thursday, June 1st. The company reported $0.56 EPS for the quarter, topping the consensus estimate of $0.18 by $0.38. MongoDB had a negative net margin of 23.58% and a negative return on equity of 43.25%. The company had revenue of $368.28 million for the quarter, compared to the consensus estimate of $347.77 million. During the same period in the previous year, the firm earned ($1.15) earnings per share. The firm’s revenue for the quarter was up 29.0% on a year-over-year basis. On average, equities research analysts expect that MongoDB, Inc. will post -2.85 earnings per share for the current year.

Insider Buying and Selling

In other MongoDB news, CTO Mark Porter sold 1,900 shares of the business’s stock in a transaction on Monday, April 3rd. The shares were sold at an average price of $226.17, for a total transaction of $429,723.00. Following the transaction, the chief technology officer now directly owns 43,009 shares of the company’s stock, valued at approximately $9,727,345.53. The sale was disclosed in a legal filing with the SEC, which can be accessed through the SEC website. In other MongoDB news, CAO Thomas Bull sold 605 shares of the business’s stock in a transaction on Monday, April 3rd. The shares were sold at an average price of $228.34, for a total transaction of $138,145.70. Following the transaction, the chief accounting officer now directly owns 17,706 shares of the company’s stock, valued at approximately $4,042,988.04. The sale was disclosed in a legal filing with the SEC, which can be accessed through the SEC website. Also, CTO Mark Porter sold 1,900 shares of the business’s stock in a transaction on Monday, April 3rd. The shares were sold at an average price of $226.17, for a total transaction of $429,723.00. Following the transaction, the chief technology officer now directly owns 43,009 shares in the company, valued at $9,727,345.53. The disclosure for this sale can be found here. Insiders have sold a total of 108,856 shares of company stock valued at $27,327,511 over the last three months. 4.80% of the stock is owned by company insiders.

About MongoDB

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MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

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Want to see what other hedge funds are holding MDB? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for MongoDB, Inc. (NASDAQ:MDB – Get Rating).

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

Posted on mongodb google news. Visit mongodb google news

Analysts at Mizuho and Stifel, among others, hiked the price target on the stock after the company unexpectedly announced a new Stream Processing offering.

“We view this as an intriguing new opportunity for the co., although it is clearly very early and remains to be seen whether MDB can meaningfully broaden its value proposition beyond databases,” wrote Mizuho analysts, who hiked the price target to $240 per share on Neutral-rated stock.

Stifel analysts are more bullish as they reiterated a Buy rating on the stock and raised the target to $420 per share.

“New announcements were very well-received by the customers and partners we spoke with during the day. Overall, with the pace of new product introductions accelerating Mongo continues to solidify its leadership position among developer data platforms,” they said in a client note.

“Net/net, the day served to reinforce our confidence in the company’s ability to sustain well above industry growth rates on its way to ~$5B of ARR (25%+ annual growth) over the next 5+ years as Mongo effectively gains new workloads (existing/future customers), benefits from an accelerating pace of AI-driven application development and sees ARPU gains as customers consume recently released/future product offerings.”

MongoDB shares closed over 4% higher yesterday.

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

Posted on mongodb google news. Visit mongodb google news

Imagine a world where the heart of technology beats in every corner, the cloud’s security umbrella spreads wide and accessibility is as universal as air.

This is the world that Guido Govers (pictured), strategic account director of ISV and high-tech partnerships at Microsoft Corp., envisions. Offering a secure cloud that’s accessible to developers far and wide is dependent on Microsoft being present everywhere, being representative in every industry and making the platform accessible to every developer.

“I think Microsoft’s strength is around making sure we’re available everywhere,” he said. “Our benefit and advantage over many of our competitors is that we’re the most secure cloud.”

Govers spoke with theCUBE industry analyst John Furrier at the MongoDB .local NYC event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed Microsoft and MongoDB’s shared focus on developer experience and integration of tools and services. (* Disclosure below.)

Toward a developer-centric world: The partnership of tech giants

Microsoft partners with MongoDB Inc., and both companies share a common mission — to create a developer-centric world. They’re working toward making their technological arsenal easily and meaningfully accessible to all, just like a toolbox that’s always within an arm’s reach.

As cutting-edge technology gets interwoven into the fabric of technology, artificial intelligence is a leading influence. Govers believes AI tech has a critical role in assisting developers in finding the content they need and focusing on their core business.

“Even the idea of Copilot; from that perspective, leveraging OpenAI and generative AI everywhere on every level,” he stated. “It’s not just on the office side of the house, but it’s also on the developer experience. How can you make it easier for developers to find the content they need? No one wants to look anymore for that little tidbit of information when you can just get that generated and focus on the actual core business.”

Govers tipped his hat to MongoDB for its unwavering commitment to developers, its drive to unify its distributed system and its belief in the power of the open-source movement.

“Developers have to keep up, and they need easier and fast to do that,” he said.

This shared appreciation for the open-source ethos and dedication to developers is driving the deep integration between MongoDB and Microsoft Azure. And as technology becomes more sophisticated, it’s clear that the most successful solutions will be those that prioritize the needs and experiences of developers.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the MongoDB .local NYC event:

(* Disclosure: TheCUBE is a paid media partner for the MongoDB .local NYC event. Neither MongoDB Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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Article originally posted on InfoQ. Visit InfoQ

NET MAUI in .NET 8 Preview 5 is available and contains bug fixes and performance improvements for cross-platform application development. It includes changes to iOS keyboard scrolling, test improvements, performance enhancements to the {Binding} mechanism and Android label layout. The announcement provoked different reactions in the community.

Visual Studio 2022 on Windows offers .NET 8 platform previews and the .NET MAUI preview workload. In order to access them, it is necessary to download version 17.7 Preview 2, select the .NET Multi-platform Application UI workload and enable the optional ‘.NET MAUI (.NET 8 Preview)’ component. For macOS users, it is recommended to download the .NET 8 preview 5 installer and install .NET MAUI using the command line.

For upgrading a .NET MAUI platform project to version 8.0.0-preview.5.8506, it is necessary to first install the .NET 8 platform SDK in the preview version. Then proceed to update the .NET MAUI NuGet packages within the project. It is possible to use Visual Studio or Visual Studio for Mac to manage the NuGet packages or manually modify the project file.

The announcement blog post sparked a lengthy discussion in the comments. Eder Cardoso wrote that all of these fixes were supposed to be on .NET 7 releases. David Ortinau, a principal product manager at Microsoft answered: 

Hi Eder, I hear you and wish we could ship all the fixes to all the versions. We are optimizing for fixing the most impactful issues and that means limiting the most all of our focus to ensuring .NET 8 is the best possible release.

Then, Eder Cardoso replied: 

All bug fixes matter David. Bug fixes are what matters the most for us as .NET MAUI developers.
Please change this bug fix merge and delivery policy/process. Bugs damage the framework’s image a lot, especially for those who are touching MAUI for the very first time.

Jens Jahrig added: 

Definitely, these fixes should have been in .NET 7.
The team does the same fairytale every year “everything will be so awesome with the next major release (5,6,7,8,9,10), we fixed so many bugs”.
But we always get a current broken version and a next version which fixes one thing and breaks another.
I see no positive change in this scheme in the last few years.

These questions and concerns show that developers are not satisfied with the development of the framework. Working with the .NET MAUI is challenging due to the number of bugs.

A full list of changes can be found in the release notes.

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MongoDB, Inc. (NASDAQ: MDB) today at its developer conference, MongoDB.local NYC, announced MongoDB Atlas for Industries, a new program to help organizations accelerate cloud adoption and modernization by leveraging industry-specific expertise, programs, partnerships, and integrated solutions. With MongoDB Atlas for Industries, customers have access to expert-led architectural design reviews, technology partnerships that deliver enhanced solutions for industry-specific challenges, and industry-specific knowledge accelerators to provide highly relevant technology training paths for development teams.

MongoDB Atlas for Industries is launching its first set of vertical solutions for financial services, an industry that is changing rapidly with shifts in automation and technology advancements.

With MongoDB Atlas, financial institutions can improve customer experiences by modernizing legacy functionality on existing in-house banking systems and building composable architectures—architectures that make it easy to integrate industry-leading software tools—to get ideas to market faster with the performance and scale they need. MongoDB Atlas for Industries programs for manufacturing and automotive, insurance, healthcare, retail and other industries will follow over the course of the year. To get started, visit mongodb.com/industries.

Tens of thousands of customers rely on MongoDB to power their applications every day, but each industry has its own unique set of challenges and needs. Many industries are also at a crossroads between being restricted by the capabilities of their legacy environments and the opportunity that is being presented by next-generation applications, data analytics, and generative AI. However, additional pressures like cost optimization can make it seem like transformation efforts are being stifled. Despite all of this, many organizations still feel a sense of urgency to modernize workloads for their most mission-critical applications and innovate quickly to remain competitive and meet customer demands. When providers can offer experts who understand the nuances and have deep experience working in a specific industry along with their technology solutions, it delivers the extra support organizations need to get started.

MongoDB Atlas for Industries provides:

• Industry Innovation Workshops – dedicated executive engagement with industry experts from MongoDB and our partners to discuss client-specific solutions using best practices developed through proven industry experience
  Industry Access Pass – access to MongoDB’s industry-specific partner integrations and toolchains to evaluate how to accelerate innovation and modernization projects
• Industry Jumpstart – building on the innovation workshops, organizations can engage with the MongoDB professional services team to accelerate a project from concept towards the production of a minimum viable product
• Industry Knowledge Accelerators – tailored MongoDB University courses and learning materials, including unlimited access to curated webinars and solutions sessions, to enable developer success

MongoDB Atlas for Financial Services

With changes in customer demands, regulatory compliance, and new players challenging incumbents, the financial services industry, which has traditionally been conservative in its adoption of new technology, is under increasing pressure to modernize applications and innovate consumer experiences. MongoDB Atlas is ideally built to help with this modernization, as well as enable organizations to build next-generation applications that take advantage of new technologies like generative AI. MongoDB Atlas also provides the resilience, scale, and highest levels of data privacy and regulatory compliance that MongoDB financial customers require.

As part of the MongoDB Atlas for Financial Services launch, MongoDB has achieved Amazon Web Services (AWS) Financial Services Competency. To obtain this competency, MongoDB was tested against strict security, operational, and reliability requirements, validating that MongoDB and AWS can help financial institutions get ideas to market faster, while reducing cost and enhancing business agility. This builds on MongoDB’s long standing relationship with AWS, including MongoDB Atlas’ availability in the AWS Marketplace. Additionally, MongoDB has become a critical foundation of the Temenos Banking Cloud, with a recent benchmark proving that together, Temenos and MongoDB can support the needs of even the largest global banks with exceptionally high performance while providing transparent data access through the JSON document model.

“Increasingly organizations in different industries are moving away from one-size-fits-all technology solutions to improve their competitive advantage and better serve customers. At MongoDB, we’ve built a team of experts with deep industry knowledge, many of whom used to be customers, so we are not only building better products with the right third party integrations, but our team can help customers get up and running faster,” said Boris Bialek, Managing Director of Industry Solutions at MongoDB. “Nineteen out of the top 20 banks in North America already use MongoDB in their infrastructure to solve some of their most critical problems. Launching Atlas for Industries is our commitment to continuing this level of dedication across financial services and other key industries.”

“MongoDB has been a trusted AWS Partner for eight years, giving customers running MongoDB Atlas on AWS a more powerful experience for building modern applications,” Mona Chadha, Director, Infrastructure Partnerships, ISVs at AWS. “Achieving the AWS Financial Services Competency reaffirms MongoDB’s commitment to AWS and financial services customers, while demonstrating their breadth and depth of financial services expertise for use cases like fraud detection and real-time payments. With MongoDB Atlas on AWS, financial institutions can optimize to reduce costs in the short term while simultaneously transforming their infrastructure for long term growth to embrace emerging technologies such as machine learning and AI.”

Temenos is an open banking platform serving 3,000 banks, from the largest financial institutions to challenger and community banks, in over 150 countries. “With partners like MongoDB, Temenos is becoming everyone’s banking platform. A platform that allows banks to elastically scale based on business demand, provide composable banking capabilities on-demand at a low cost, while reducing their environmental impact,” said Tony Coleman, Chief Technology Officer at Temenos. “We recently conducted a performance benchmark with MongoDB proving the capability of Temenos’ platform to power the world’s biggest banks and their BaaS offerings with hundreds of millions of customers, efficiently and sustainably in the cloud.”

Wells Fargo is a leading financial services company with approximately $1.9 trillion in assets, serving one in three US households and more than 10% of small businesses in the US. “When we look for new solutions it’s not just about what the technology can enable us to do, but it is about finding a partner who can help us get the most out of the technology, with expertise in our industry, to help us work through our specific challenges and deliver solutions for our advisors and clients with agility,” said Munish Kumar, Chief Information Officer of Wealth and Investment Management at Wells Fargo.

Michael Liersch, Head of Advice and Planning at Wells Fargo, agrees. “MongoDB’s experience in working with financial services organizations and as a leading developer data platform enables Wells Fargo to deliver innovative financial advice, like our new LifeSync platform, which provides a personalized digital approach to aligning our clients’ goals with their money.”

A global leader in consulting and technology services, Capgemini has been enabling business transformation for more than 50 years and work with eight of the top 15 banks and nine of the top 15 diversified financial companies.

“Working together, Capgemini and MongoDB have been enabling business critical modernization and innovation initiatives in leading financial services customers across the world with a focus on increasing performance in a cost effective way,” said Nilesh Vaidya, Global Industry Head – Retail Banking and Wealth Management at Capgemini. “Our teams are also closely working together to meet new challenges that are on the horizon. We have developed unique accelerators and are actively designing the next generation of AI and ML enabled solutions to help our customers differentiate.”

Bendigo and Adelaide Bank is one of Australia’s biggest banks, with more than 7,000 employees helping over 1.9 million customers.

“The expertise that MongoDB delivered from working with other large customers in financial services combined with the MongoDB Atlas developer data platform, was vital in helping us transform our organization for the future,” said Matt Vermeer, Cloud Platforms Service Owner at Bendigo and Adelaide Bank. “We believe our partnership with MongoDB will help us accelerate this continued transformation of our business, deliver our technology strategy, and ultimately grow our organization to achieve our vision of becoming Australia’s bank of choice by feeding into the prosperity of customers and their communities.”

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

Posted on mongodb google news. Visit mongodb google news

To Andrew Davidson, senior vice president of products at MongoDB, the database business operates in an entirely different type of market than traditional software, where vendors might sell their products into one organization after another, eventually reaching a saturation point. They can grow fast, but it’s tough to keep that growth going after a while.

With databases – MongoDB since 2007 has been a staple in the NoSQL market with its MongoBD document-oriented database – it’s about capturing workloads, so the vendor’s business grows as the number of enterprise workloads expands. And in an era of exploding amounts of data, cloud computing, and the accelerated rise of generative AI, the number of workloads will only skyrocket.

“Software in many ways is defining the economy today,” Davidson told journalists in the runup to this week’s MongoDB.local developer conference in New York City. “If software is defining the economy today, then in many ways we’re in a developer-defined economy. Developers make all this possible and they’re picking the software technologies that make up the back end of the software. Databases, for example, to power all these applications and all of these new technologies, whether it’s what we’ve seen over the last couple of years with low code [and] no code or what we’re seeing over the last twelve months, that tipping point moment for AI. All of this will accelerate and democratize the trend of more and more software, more and more application workloads that will be built all over the world.”

MongoDB plans to get its share of this business, which will be important as the company looks to reach that nirvana that is profitability. As we noted here earlier this year, MongoDB, like other database and storage companies, is still waiting to reach that plateau, despite being the dominant NoSQL database company and counting more than 40,800 customers and having $1.8 billion on hand.

A key for the company will be its Atlas cloud database, a fully managed service that runs on Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Atlas revenue in FY 2023 grew 65.4 percent year-over-year, hitting $810.6 million. Subscriptions for all of MongoDB’s businesses jumped 46.7 percent while services rose 541 percent.

Given all that, it’s not surprising that MongoDB at its event this week is pushing out new functionality in Atlas, nor is it surprising that a good portion of that touches on generative AI, which Davidson – like most others in IT – said will be the next big paradigm shift in tech, after mainframes, PCs, client-server, cloud, and mobile. It will rapidly automate software development, from code generation to testing to debugging, all of which will require data-intensive applications and more data, all in more real-time operational use cases demanding continuous availability.

“It’s going to be increasingly possible to take advantage of multimedia use cases, images, video, audio and geospatial and more, and to do interesting, meaningful things with them,” he said. “And all of this is in service of incredible applications that are going to be extremely powerful and valuable in every industry. New user experiences, natural language processing, and more. We see AI as a driver for economic value in the form of new applications in every industry, and we’re going to be part of that trend.”

MongoDB in part will do this through expanding a partnership with Google Cloud that started in 2018, integrating Google Cloud’s two-year-old Vertex AI large-language models (LLMs) and managed machine learning platform with Atlas to accelerate developers’ work creating AI-based software. MongoDB also is introducing Atlas Vector Search, a tool for enterprises to more easily use LLMs, which require that the data they use come in vectors. Rather than specific keywords as in traditional search, vector search uses semantic meaning and similarity between vectors for retrieving data, building sentences from prompts, or generating images. It’s a concept that’s been around for a while, Davidson said.

“But something’s really changed over the last two years or so and that is, while in the past we needed to have hard-core machine learning and data science chops to do any of this, now folks have been able to take advantage of off-the-shelf models – many of which are open source – that can summarize rich source data that could be text or images or video or sound, and it could summarize these models as inference models, summarize that data into what are called ‘vector embeddings,’ which is a numerical representation or summary of that information,” he said.

Organizations are using specialized databases for storing vectors that LLMs can use, but with Vector Search in Atlas, they can use MongoDB’s cloud-based database. In addition, Vector Search – which is in public preview – opens up new workloads to run on Atlas, including text-to-image.

AI also will accelerate application modernization, so MongoDB is working to make it easier for enterprises to move off more traditional relational databases – which remains the vendor’s key competitors – to its NoSQL platforms. Such migrations aren’t easy, requiring sorting through workloads, updating schemas, modernizing code, and rewriting applications. For MongoDB, they’re important. Davidson said about a third of the company’s business comes from app modernization efforts.

MongoDB last year previewed Relational Migrator, a tool to make that move easier and now is making it generally available. The tool analyzes other databases – Oracle, Microsoft SQL Server, MySQL, and PostgreSQL, among others – and automatically recommends a new data schema. It then transforms the data, migrates it to MongoDB Atlas, and generates code to work with modern applications.

MongoDB is stretching that thinking into the future and is working on a SQL query conversation capability for converting code to MongoDB’s query language. In addition, its engineers are investigating ways to more easily convert application software to work with MongoDB Atlas, he said.

MongoDB also is adding in public preview Search Nodes to Atlas, creating a dedicated infrastructure with optimized hardware for scaling search workloads independent of the database. “We’ve realized is we’re being pulled in the direction of servicing more and more mission-critical, at-scale use case for search,” Davidson said. “This is going to pave us a road into much larger scale use cases in the future.”

Atlas Stream Processing, also in preview, is aimed at processing streaming data like that coming from Web browsing and Internet of Things devices. In addition, organizations can now use Atlas Online Archive and Atlas Data Federation to query Azure Blob Storage, something that MongoDB previously had enabled in AWS.

MongoDB is hoping such new capabilities will keep customers on the Atlas cloud platform and attract new ones as the software field continues to evolve with generative AI and other emerging technologies. The company holds about 44 percent of the NoSQL database space today, but there are strong competitors, including AWS DynamoDB and Apache Cassandra.

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

Posted on mongodb google news. Visit mongodb google news

Data is multifarious. Information is used in so many places for so many technology applications and use cases that it takes on many forms, it runs at many speeds, it resides in many types of storage structures and it represents different levels of mission-critical value. Because there is now such an (almost) infinite variety of data spread across the enterprise, organizations need a way to not perform many different types of queries across data-in-motion and data-at-rest.

Even when we think we have a handle on the ‘shape’ of the information wave that travels across our new digital workflows, firms can experience unexpected spikes, outages and disruptions that throw the best-laid plans out of kilter. These home truths have an impact on the way the technology industry has been working to adapt databases work; when we also factor in the new reality of generative AI, there’s a lot to ingest here – and we haven’t even started on data ingestion challenges here.

It’s all very well if the database vendors tell us they can now offer more speed, performance and agility (and they do – yawn), what we now need is deeper specific insight into the way the engine room functions, what kind of gearing ratios we can make use of and whether or not we’re kitted out with all-terrain road tires. Developer data platform company MongoDB, Inc. says it has watched all the above factors play out in order to extend its core technology proposition this year.

The company talks about its focus on operational data across an entire organization, for any workload or use case. That means working data, live data, real-time data and every information stream that exists all the way through to the fragmented unstructured data that resides in the murky waters of the data lake, or perhaps (certainly in MongoDB’s case) the more ordered confines of the data lakehouse.

A developer data platform

As noted above, MongoDB generally doesn’t refer to its technology as a database, the company calls MongoDB Atlas a developer data platform. This means it is a technology built from database foundations, but now significantly more directly engineered for so-called modern applications i.e. ones that feature potentially massive data flows, ones that make heavy use of automation and autonomous management where possible, ones that are eminently scalable, flexible, resilient and agile when the need for impactful change (remember Covid-19?), ones that embrace microservices and containerization for granular control, ones that have the ‘luxury’ of serverless provisioning and – basically – ones that don’t look like the monolithic applications we built before 1999.

“When we talk about MongoDB Atlas as a developer data platform, we mean that we offer developers everything they need to work with data – a task which typically takes up some three-quarters of their time when working to provision and manage the infrastructure for the enterprise applications that we all depend upon,” said Dev Ittycheria, president and CEO at MongoDB.

So that’s a developer data platform then and not a data developer platform, the latter (if it were to exist) presumably being something that Database Administrators (DBAs) might use to perform the Ops-operations roles that they fulfil in DevOps teams. If anything, says Ittycheria, MongoDB has ‘obviated’ (in a positive way) the need for DBAs to focus on many of the traditional grunt work jobs associated with operations so they can instead turn their attention to higher value tasks such as identifying bottlenecks or looking for operational efficiencies and so on.

“Cloud has enabled such a wide variety of use cases across increasingly diverse application structures, but there have inevitably been trade-offs with an explosion of ‘point tools’ designed to handle specific functions – such as text search, graph queries, time-series functions, vector-based search and more – a reality that always means there will be diminishing returns in terms of what a developer can do with a tool in any one deployment scenario. By offering essential developer data functions in MongoDB Atlas built natively [such as vector-search, explained later in this story], we can offer all the benefits of cloud in a radically simplified and unified model,” clarified Ittycheria, with a degree of quiet confidence when speaking to press this summer 2023.

New this summer from MongoDB are new products and features including generative AI capabilities with MongoDB Atlas Vector Search for ‘highly’ relevant information retrieval and personalization, MongoDB Atlas Search Nodes for dedicated resources with search workloads at enterprise scale, MongoDB Atlas Stream Processing for high-velocity streams of complex data, significant scaling and efficiency improvements for MongoDB Time Series collections and new capabilities using MongoDB Atlas Data Federation for querying data and isolating workloads on Microsoft Azure.

If that penny didn’t drop there… this is all about standardizing many types of workloads on a single developer data platform across the enterprise. As we said at the start, data is multifarious.

“The new MongoDB Atlas capabilities are an answer to the feedback we get from customers every day; they love that their teams are able to quickly build and innovate with MongoDB Atlas and want to be able to do even more with it across the enterprise,” said CEO Ittycheria. “With the [platform’s] new features, we’re further supporting customers running the largest, most demanding mission-critical workloads that require continually increasing scalability and flexibility, so they can unleash the power of software and data with next-generation applications.”

What’s all the fuss with data?

To the casual non-techie not particularly interested in data science that just wants their business applications to work, it might well sound like the technology industry is being a bit histrionic over the ‘new’ data streams that we need to deal with. After all, this isn’t the 1950s and we’ve long moved on from the era of punch cards, mainframes (apart from their use in financials) and the early clunky use of data systems with basic storage and retrieval functionalities and only limited scope for analytics.

Much of the answer comes down to the widely touted inflexion point that we now find ourselves in. There’s the rise (some would say explosion) of new technology like generative AI and Large Language Models (LLMs) and the widespread (some would say exponential) growth of different types of data being generated in real-time. Combine that data back-end reality with the front-end demands of users who have gotten well-used to instant application functions and updates, which are largely driven by ubiquitous connectivity, the always-on model of the cloud and the ability for software developers to deliver continuous integration and continuous deployment – and you can see why we need more than just a database these days.

To be fair to MongoDB, every other data vendor out there refers to their technology as a platform, but it’s worth knowing why this progression to a more unified and fully managed developer data platform has taken place.

The integrated functionality factor

According to the company’s engineering team, MongoDB Atlas today represents a multi-cloud developer data platform that provides an integrated set of data and application services in a unified environment to enable developer teams to quickly build with the capabilities, performance and scale modern applications require. CEO Ittycheria notes that this essentially ‘integrated functionality factor’ is what more companies today have been asking for

Core product updates for MongoDB this year include a number of key cornerstone technologies.

To integrate AI-powered search and personalization into applications on MongoDB Atlas, the company has developed MongoDB Atlas Vector Search. Surfacing as a comparatively new term in enterprise technology circles (although stemming from computer science principles that have been around for decades) the world of vector search makes use of Machine Learning (ML) techniques in order to understand the contextual meaning behind more unstructured types of data such as video or images, but often also text. By transforming meaning values into geometric representations in the shape of vectors, machines can plot out our wider but specific human intent when we engage in search and then start analytics procedures to discover results for us.

The previously noted use of Large Language Models (LLMs) requires data in the form of vectors. According to MongoDB, these types of AI models measure the similarity between vectors to probabilistically construct sentences from prompts, generate images from captions, or return search results that are more accurate and contain greater context than traditional search engines.

“To store vectors so LLMs can use them, some organizations have begun using specialized databases. However, single-purpose databases for use cases like vector stores or time-series applications are often bolted on to existing technology stacks, resulting in more administrative complexity, an educational burden on developers, and longer time to value. With MongoDB Atlas Vector Search, customers can power a range of new workloads from semantic search with text to image search and comparison to highly personalized product recommendations using a single, familiar, unified platform across an entire organization – all with minimal developer friction,” notes the company, in a technical statement.

MongoDB Atlas Vector Search also allows customers to securely augment the capabilities of pre-trained generative AI models with their own data to provide memory that creates more accurate and relevant results for specific domains or use cases.

Other base-level developments from MongoDB for this year’s platform update also include the ability to scale search workloads independent of their database – remember how ‘scale’ was one of the defining factors of a modern application? The company has also engineered for the ability to process high-velocity streams of complex data with MongoDB Atlas, so with data stream processing also being fundamental to the way data platforms must now develop, this is arguably expected but also welcome.

Data tiering, without tears

It’s also worth noting that MongoDB has enabled ‘tier and query data’ on Microsoft Azure with MongoDB Atlas Online Archive and Atlas Data Federation. New multi-cloud options bring Microsoft Azure support to MongoDB Atlas Online Archive and Atlas Data Federation in addition to Amazon Web Services (AWS).

As explained in full here “A tiered [data] storage architecture categorizes data hierarchically based on its business value, with data ranked by how often it’s accessed by users and applications.”

Often classified by whether data is ‘hot’ (frequently used, mission-critical and essential for modern application processing) or ‘cold’ (less used, so suitable for cheaper forms of slower data storage services with more latency overhead and so, therefore, slower recovery), data tiering enables us to work with more types of information more cost-effectively. Given the different types of data that we have been talking about here and the fact that many different types of cloud services are available in the multi-cloud world, data tiering has evolved from being a useful spanner to a keenly sharpened tool in the cloud data engineer’s toolbox these days.

As per the organization’s announcement statement for this news, “Customers today use MongoDB Atlas Online Archive to automatically tier Atlas databases to the most cost-effective cloud object storage option while retaining the ability to query with high performance. By adding support for Microsoft Azure, customers can now more easily keep their entire workloads in the same cloud. Atlas Data Federation provides a way to read and write data from Atlas databases and cloud object stores to simplify how customers can generate datasets from Atlas to feed downstream applications and systems that use cloud storage.”

Data trends to take away

As we said at the start, data is multifarious. There’s a lot more data in a lot more places in a lot more ‘form factors’ today, all tasked with doing a lot more jobs across many more clouds, applications and ancillary services. To reflect and ‘serve’ our user needs across this seemingly vast information topography, MongoDB has perhaps described a more diverse set of platform tools, functions and abilities.

What matters now is whether these tools are useable by the data-centric developers who will need to get their hands dirty with it – but there’s integrated platform-wide automation now, so it’s a much less dirty job. The world of data is certainly humongous, how on earth could MongoDB have come up with that name right?

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

Posted on mongodb google news. Visit mongodb google news

Dow Jones futures fell slightly overnight, along with S&P 500 futures and Nasdaq futures. The Nasdaq composite and the S&P 500 rose Thursday, but it was a mixed session for the stock market rally, with weak broadside.

X

Megacaps were strong. Amazon.nl (AMZN) took the lead as Amazon Web Services announced new artificial intelligence efforts. AMZN stock hit a nine-month high after the AWS cloud unit unveiled a $100 million investment in generative AI to help customers. Loop Capital expects the AWS growth slowdown to “bottom” soon. That sentiment could also be good news for cloud rivals Microsoft (MSFT), Google parent Alphabet (GOOGL), both of which had solid sessions.

MongoDB (MDB), Super micro computer (SMCI) and Lamb research (LRCX) made bullish bounces on Thursday. The trio put up aggressive entries even though they came off intraday highs.

A number of software and chip plays produced solid moves on Thursday.

C3.ai (KI) and Samsara (IOT), two AI stock games held investor day events. AI shares fell 4.1% on Thursday, testing their 21-day line. IOT shares gained 1.2% after a four-day decline. But it’s unclear whether the investor day events had a significant impact on either stock. Analysts’ reaction could move shares of C3.ai and IOT on Friday.

Bank stocks were remarkably weak, from PacWest Bancorp (PACW) to JPMorgan Chase (J.P.M.). There was no clear trigger or clear signs of a renewed deposit flight, but banks are facing long-term problems that could curb long-term profitability.

Don’t overthink it. Thursday was likely a modest, mixed upturn within a modest pullback with a solid tech-led stock market rally.

MDB shares were added to IBD Leaderboard on Thursday and are listed on the IBD Big Cap 20. LRCX shares have joined SwingTrader. MongoDB and IOT stocks are on the IBD 50. Lam Research was the IBD stock of the day on Thursday.

Dow Jones Futures Today

Dow Jones futures fell 0.2% from fair value, even with 3M (MMM) stumble upon a major settlement over chemicals in drinking water. S&P 500 futures fell 0.25% and Nasdaq 100 futures fell 0.3%.

Remember that overnight action in Dow futures and elsewhere does not necessarily translate into actual trading in the next regular trading session.

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

Stock market rally

The stock market rally had a mixed session as tech giants and AI games rebounded. The Dow Jones Industrial Average closed fractionally lower during stock market trading on Thursday. The S&P 500 index climbed 0.4%. The Nasdaq composite gained 0.95%. The small-cap Russell 2000 fell 0.8%.

Amazon shares rose 4.3% to 130.15.

Apple (AAPL), Microsoft, Google, Tesla (TSLA), Taiwan semiconductor (TSM) and Salesforce. com (CRM) all increased by 1.5% to just above 2%.

US crude oil prices fell 4.2% to $69.51 a barrel. The yield on 10-year Treasury bills rose 8 basis points to 3.8%.

ETFs

Among growth ETFs, the Innovator IBD 50 ETF (FFTY) rose 0.4%. The iShares Expanded Tech-Software Sector ETF (IGV) rose 0.55%. The VanEck Vectors Semiconductor ETF (SMH) rose 0.55%. LRCX stock is a notable SMH holding company.

Reflecting more speculative story stocks, ARK Innovation ETF (ARKK) closed just above break-even and ARK Genomics ETF (ARKG) fell 1%.

SPDR S&P Metals & Mining ETF (XME) and the Global X US Infrastructure Development ETF (PAVE) both fell 0.6%. US Global Jets ETF (JETS) maintained high. SPDR S&P Homebuilders ETF (XHB) fell 0.5%. The Energy Select SPDR ETF (XLE) fell 1.3% and the Health Care Select Sector SPDR Fund (XLV) rose 0.7%.

The Financial Select SPDR ETF (XLF) fell 0.8%. JPM shares lost 1.9% near the 50-day line after testing a buy point on Wednesday. The SPDR S&P Regional Banking ETF (KRE) tumbled 3.2% to fall below the 50-day line. The PACW share fell by 5.9%.

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Stocks to watch

MDB shares rose 4.1% on Thursday to 388.36 in heavy volume, breaking a trendline in a three-week tight pattern in what could be a high tight flag. That offered an early entry around 385 or maybe 389. That’s after initially testing the low of its recent range since the huge earnings gap on June 2. The MongoDB share rose to 396.84. The database software maker announced an expanded relationship with Google Cloud, as well as several AI initiatives. MongoDB also works with Amazon Web Services, among others.

SMCI stock bounced 3% to 226.46, moving off its 21-day moving average in strong trading. An aggressive trader could have used a move above Wednesday’s high of 227 as an early entry. However, stocks encountered resistance on the 10-day line, trailing well behind the highs of 241.97 and closing just below the aggressive buy point.

LRCX shares rose 2.3% to 619.87 after initially undercutting the 21-day line and the 600 level. Investors could have used a move above Wednesday’s high of 615.80 as an entry point. The shares retreated from intraday highs of 624.48, right around a short-term trendline. LRCX shares, like MongoDB, are working a tight three-week period with an official buy point of 644.60. Some other chip gear giants bounced off their 21-day lines.

Analysis of the market rally

The stock market rally ended the recent decline on Thursday with a slight bounce. The Nasdaq and the S&P 500 both came out of their 10-day lines, led by Amazon and other growth giants.

So is the Nasdaq pullback over after three days? If so, it would be extended again soon, raising expectations for another pullback. The Nasdaq closed at 7.8% above its 50-day line on Thursday, with the Nasdaq 100 at 9.1%.

Broadside was noticeably weak given the solid Nasdaq bounce. Losers trump winners 2-to-1 on the NYSE and 8-to-5 on the Nasdaq.

The Dow Jones and Russell 2000 tested their 21-day lines on Thursday.

The Invesco S&P 500 Equal Weight ETF (RSP) fell 0.4%, just above the 21-day mark, while the S&P 500 posted modest gains. The First Trust Nasdaq 100 Equal Weighted Index ETF (QQEW) climbed 0.25%, well behind the Nasdaq 100’s 1.2% pop.

Hottech stocks bounced off support levels including MDB stocks and SMCI. That’s what you want to see when the Nasdaq rises. If the Nasdaq resumes a decline, you want these names to withstand the selling pressure.

Several stocks are consolidating around traditional buying points such as Monday. com (MNDY) and Parker-Hannifin (PH).

Time the market with IBD’s ETF market strategy

What to do now

If you are an aggressive trader, you could have bought shares of MongoDB, Lam Research, SMCI or a few other recovering stocks on Thursday. It is much less risky to add a few stocks to an existing bet than to start a new position. If a Nasdaq pullback resumes, many of these leaders could relapse. If you buy a bounce near intraday highs, it doesn’t take much to be underwater.

A swing trader’s mindset makes sense for new or additional purchases, cutting losses quickly and taking partial profits early to lock in some profits. If the stock continues to move forward, you can keep the remaining stock as position trades.

Whether you pull the trigger or not, you definitely want to look at big winners, looking for those holding support or bouncing back. Keep your watchlists up-to-date from different industries. It remains important to use early entries and buy close to those entries.

Read The Big Picture every day to stay in sync with market direction and leading stocks and sectors.

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

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