Mini book: Act One: From Chatbots to AI Agents

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Article originally posted on InfoQ. Visit InfoQ

The Act One: From Chatbots to AI Agents eMag  marks a pivotal moment in the evolution of artificial intelligence, a shift from the familiar realm of chatbots to the more dynamic and autonomous world of AI agents. We’ve curated a collection of articles that explore this exciting transition, offering both practical insights and forward-looking perspectives on the challenges and opportunities that lie ahead. This paradigm shift has the potential to revolutionize industries, but also demands a new set of tools, techniques, and ethical considerations.

This edition offers a glimpse into the transformative potential of AI agents. We believe this is just the beginning of a much longer story. We invite you to join us on this journey as we continue to explore the exciting world of AI and its profound impact on our future.

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Nvidia Unveils AI, GPU, and Quantum Computing Innovations at GTC 2025

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MMS Daniel Dominguez

Article originally posted on InfoQ. Visit InfoQ

Nvidia presented a range of new technologies at its GTC 2025 event, focusing on advancements in GPUs, AI infrastructure, robotics, and quantum computing. The company introduced the GeForce RTX 5090, a graphics card built on the Blackwell architecture, featuring improvements in energy efficiency, size reduction, and AI-assisted rendering capabilities. Nvidia highlighted the increasing role of AI in real-time, path-traced rendering and GPU performance optimization.

In the data center sector, Nvidia announced the Blackwell Ultra GB300 family of GPUs, designed to enhance AI inference efficiency with 1.5 times the memory capacity of previous models. The company also introduced MVLink, a high-speed interconnect technology that enables faster GPU communication, and Nvidia Dynamo, an AI data center operating system aimed at improving management and efficiency. The DGX Station, a computing platform for AI workloads, was also unveiled to support enterprise AI development.

Nvidia’s automotive division revealed a partnership with General Motors to develop AI-powered self-driving vehicles. The company stated that all software components involved in the project have undergone rigorous safety assessments. Additionally, Nvidia introduced Halos, an AI-powered safety system for autonomous vehicles, integrating hardware, software, and AI-based decision-making.

In robotics, Nvidia introduced the Isaac GR00T N1, an open-source humanoid reasoning model developed in collaboration with Google DeepMind and Disney Research. The Newton physics engine, also open-source, was announced to enhance robotics training by simulating real-world physics for AI-driven robots. Nvidia also expanded its Omniverse platform for physical AI applications with the launch of Cosmos, a generative model aimed at improving AI-driven world simulation and interaction.

The company announced new AI models under the Llama Nemotron family, designed for reasoning-based AI agents. These models are optimized for enterprises looking to deploy AI agents that can work autonomously or collaboratively. Nvidia stated that members of the Nvidia Developer Program could access Llama Nemotron for development, testing, and research.

Nvidia revealed its latest advancements in quantum computing, including the launch of the Nvidia Accelerated Quantum Research Center in Boston. The company is collaborating with Harvard and MIT on quantum computing initiatives. During the conference, Nvidia hosted Quantum Day, where CEO Jensen Huang discussed the evolving role of quantum computing and acknowledged previous underestimations of its development timeline. 

The company introduced a roadmap for future GPUs, including the Vera Rubin GPU, set for release in 2026, followed by Rubin Ultra NVL576 in 2027, which is projected to deliver 15 exaflops of computing power. Nvidia also announced the Feynman GPU, scheduled for 2028, designed to advance AI workloads with enhanced memory and performance capabilities.

Following the conference, online discussions reflected various perspectives on Nvidia’s announcements. Many users expressed interest in the concept of physical AI and its potential applications. 

AI expert Armughan Ahmad shared:

AI is shifting from simple chat assistants to autonomous agents that execute work on our behalf.

While AI strategist Vivi Linsi commented:

With the arrival of agentic and physical AI, AI has developed from talking to Doing – are you ready?

Nvidia’s announcements at GTC 2025 highlight the company’s continued investment in AI, data centers, robotics, and quantum computing, positioning itself at the forefront of next-generation computing infrastructure.

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Sei Investments Co. Sells 142,830 Shares of MongoDB, Inc. (NASDAQ:MDB) – MarketBeat

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Sei Investments Co. lessened its holdings in shares of MongoDB, Inc. (NASDAQ:MDBFree Report) by 56.9% during the 4th quarter, according to the company in its most recent disclosure with the SEC. The institutional investor owned 108,209 shares of the company’s stock after selling 142,830 shares during the quarter. Sei Investments Co. owned approximately 0.15% of MongoDB worth $25,193,000 at the end of the most recent reporting period.

A number of other institutional investors have also recently added to or reduced their stakes in MDB. Intech Investment Management LLC raised its holdings in MongoDB by 10.7% in the 3rd quarter. Intech Investment Management LLC now owns 5,205 shares of the company’s stock worth $1,407,000 after acquiring an additional 502 shares during the period. Charles Schwab Investment Management Inc. increased its stake in shares of MongoDB by 2.8% in the third quarter. Charles Schwab Investment Management Inc. now owns 278,419 shares of the company’s stock worth $75,271,000 after purchasing an additional 7,575 shares during the period. Cerity Partners LLC lifted its position in shares of MongoDB by 8.3% during the 3rd quarter. Cerity Partners LLC now owns 9,094 shares of the company’s stock worth $2,459,000 after purchasing an additional 695 shares during the last quarter. Daiwa Securities Group Inc. boosted its stake in MongoDB by 12.3% during the 3rd quarter. Daiwa Securities Group Inc. now owns 10,323 shares of the company’s stock valued at $2,791,000 after purchasing an additional 1,132 shares during the period. Finally, Independent Advisor Alliance grew its holdings in MongoDB by 5.3% in the 3rd quarter. Independent Advisor Alliance now owns 1,516 shares of the company’s stock valued at $410,000 after buying an additional 76 shares during the last quarter. 89.29% of the stock is currently owned by institutional investors and hedge funds.

MongoDB Stock Performance

Shares of MDB stock opened at $193.66 on Thursday. The stock’s fifty day moving average is $248.25 and its 200-day moving average is $267.64. MongoDB, Inc. has a 52 week low of $173.13 and a 52 week high of $387.19. The stock has a market capitalization of $14.42 billion, a PE ratio of -70.68 and a beta of 1.30.

MongoDB (NASDAQ:MDBGet Free Report) last posted its quarterly earnings data on Wednesday, March 5th. The company reported $0.19 earnings per share for the quarter, missing the consensus estimate of $0.64 by ($0.45). MongoDB had a negative net margin of 10.46% and a negative return on equity of 12.22%. The company had revenue of $548.40 million during the quarter, compared to analyst estimates of $519.65 million. During the same quarter in the previous year, the business posted $0.86 EPS. As a group, analysts forecast that MongoDB, Inc. will post -1.78 earnings per share for the current fiscal year.

Insider Buying and Selling

In related news, insider Cedric Pech sold 287 shares of MongoDB stock in a transaction dated Thursday, January 2nd. The stock was sold at an average price of $234.09, for a total value of $67,183.83. Following the completion of the sale, the insider now directly owns 24,390 shares in the company, valued at $5,709,455.10. This trade represents a 1.16 % decrease in their ownership of the stock. The sale was disclosed in a document filed with the Securities & Exchange Commission, which can be accessed through the SEC website. Also, CAO Thomas Bull sold 169 shares of the company’s stock in a transaction dated Thursday, January 2nd. The shares were sold at an average price of $234.09, for a total transaction of $39,561.21. Following the transaction, the chief accounting officer now owns 14,899 shares in the company, valued at approximately $3,487,706.91. The trade was a 1.12 % decrease in their ownership of the stock. The disclosure for this sale can be found here. Insiders sold 43,139 shares of company stock worth $11,328,869 in the last quarter. Insiders own 3.60% of the company’s stock.

Wall Street Analysts Forecast Growth

A number of equities analysts recently issued reports on MDB shares. Truist Financial dropped their target price on shares of MongoDB from $400.00 to $300.00 and set a “buy” rating on the stock in a research report on Thursday, March 6th. UBS Group set a $350.00 price objective on shares of MongoDB in a research report on Tuesday, March 4th. Guggenheim raised MongoDB from a “neutral” rating to a “buy” rating and set a $300.00 target price on the stock in a research report on Monday, January 6th. Wells Fargo & Company cut MongoDB from an “overweight” rating to an “equal weight” rating and cut their price target for the company from $365.00 to $225.00 in a report on Thursday, March 6th. Finally, Tigress Financial lifted their price objective on MongoDB from $400.00 to $430.00 and gave the stock a “buy” rating in a report on Wednesday, December 18th. Seven research analysts have rated the stock with a hold rating and twenty-three have assigned a buy rating to the company. According to data from MarketBeat, the stock currently has a consensus rating of “Moderate Buy” and a consensus target price of $320.70.

Read Our Latest Analysis on MDB

MongoDB Company Profile

(Free Report)

MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides 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-premises, 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:MDBFree Report).

Institutional Ownership by Quarter for MongoDB (NASDAQ:MDB)

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Quantbot Technologies LP Makes New Investment in MongoDB, Inc. (NASDAQ:MDB)

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Quantbot Technologies LP acquired a new stake in MongoDB, Inc. (NASDAQ:MDBFree Report) in the 4th quarter, according to its most recent Form 13F filing with the Securities & Exchange Commission. The institutional investor acquired 3,016 shares of the company’s stock, valued at approximately $702,000.

Several other hedge funds and other institutional investors have also modified their holdings of MDB. Hilltop National Bank raised its stake in MongoDB by 47.2% during the 4th quarter. Hilltop National Bank now owns 131 shares of the company’s stock valued at $30,000 after purchasing an additional 42 shares during the last quarter. Brooklyn Investment Group acquired a new position in shares of MongoDB during the third quarter valued at about $36,000. Continuum Advisory LLC lifted its stake in shares of MongoDB by 621.1% in the third quarter. Continuum Advisory LLC now owns 137 shares of the company’s stock valued at $40,000 after buying an additional 118 shares during the period. NCP Inc. acquired a new stake in MongoDB during the fourth quarter worth about $35,000. Finally, Wilmington Savings Fund Society FSB bought a new position in MongoDB during the third quarter valued at about $44,000. Institutional investors and hedge funds own 89.29% of the company’s stock.

Analyst Upgrades and Downgrades

MDB has been the topic of a number of research reports. Guggenheim upgraded MongoDB from a “neutral” rating to a “buy” rating and set a $300.00 price objective on the stock in a research report on Monday, January 6th. DA Davidson boosted their price target on shares of MongoDB from $340.00 to $405.00 and gave the company a “buy” rating in a report on Tuesday, December 10th. JMP Securities reaffirmed a “market outperform” rating and set a $380.00 price objective on shares of MongoDB in a report on Wednesday, December 11th. KeyCorp cut shares of MongoDB from a “strong-buy” rating to a “hold” rating in a research note on Wednesday, March 5th. Finally, Rosenblatt Securities restated a “buy” rating and set a $350.00 price target on shares of MongoDB in a research note on Tuesday, March 4th. Seven equities research analysts have rated the stock with a hold rating and twenty-three have given a buy rating to the company. According to MarketBeat.com, MongoDB has an average rating of “Moderate Buy” and a consensus target price of $320.70.

View Our Latest Report on MDB

Insider Activity at MongoDB

In other news, CEO Dev Ittycheria sold 2,581 shares of the company’s stock in a transaction dated Thursday, January 2nd. The stock was sold at an average price of $234.09, for a total value of $604,186.29. Following the completion of the sale, the chief executive officer now directly owns 217,294 shares of the company’s stock, valued at $50,866,352.46. This represents a 1.17 % decrease in their position. The sale was disclosed in a legal filing with the SEC, which is available through this hyperlink. Also, CAO Thomas Bull sold 169 shares of MongoDB stock in a transaction that occurred on Thursday, January 2nd. The stock was sold at an average price of $234.09, for a total transaction of $39,561.21. Following the transaction, the chief accounting officer now directly owns 14,899 shares in the company, valued at $3,487,706.91. The trade was a 1.12 % decrease in their position. The disclosure for this sale can be found here. Insiders have sold 43,139 shares of company stock worth $11,328,869 over the last ninety days. Company insiders own 3.60% of the company’s stock.

MongoDB Stock Down 2.5 %

MDB stock opened at $193.66 on Thursday. MongoDB, Inc. has a twelve month low of $173.13 and a twelve month high of $387.19. The company has a market cap of $14.42 billion, a P/E ratio of -70.68 and a beta of 1.30. The business has a fifty day moving average of $248.25 and a 200-day moving average of $267.64.

MongoDB (NASDAQ:MDBGet Free Report) last announced its quarterly earnings data on Wednesday, March 5th. The company reported $0.19 earnings per share for the quarter, missing the consensus estimate of $0.64 by ($0.45). The firm had revenue of $548.40 million for the quarter, compared to the consensus estimate of $519.65 million. MongoDB had a negative return on equity of 12.22% and a negative net margin of 10.46%. During the same period in the prior year, the firm posted $0.86 earnings per share. As a group, equities research analysts anticipate that MongoDB, Inc. will post -1.78 earnings per share for the current fiscal year.

MongoDB Company Profile

(Free Report)

MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides 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-premises, 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.

Featured Stories

Institutional Ownership by Quarter for MongoDB (NASDAQ:MDB)

This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest and most accurate reporting. This story was reviewed by MarketBeat’s editorial team prior to publication. Please send any questions or comments about this story to contact@marketbeat.com.

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MarketBeat keeps track of Wall Street’s top-rated and best performing research analysts and the stocks they recommend to their clients on a daily basis. MarketBeat has identified the five stocks that top analysts are quietly whispering to their clients to buy now before the broader market catches on… and MongoDB wasn’t on the list.

While MongoDB currently has a Moderate Buy rating among analysts, top-rated analysts believe these five stocks are better buys.

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Palantir (PLTR) and MongoDB (MDB) Defy Software Sector Downtrend – GuruFocus

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According to Morgan Stanley, the overall performance of the U.S. software sector has deteriorated in the fourth quarter. However, infrastructure software companies like Palantir (PLTR, Financial) and MongoDB (MDB) have bucked the trend, achieving strong revenue growth for the second consecutive quarter.

Analysts led by Keith Weiss at Morgan Stanley reported a decline in revenue, operating margins, and earnings per share across the software industry. The percentage of companies exceeding market expectations by 1% dropped, and the median extent of exceeding expectations turned negative after two quarters of improvement, falling below historical averages. For instance, 64% of companies exceeded revenue expectations by more than 1%, down from 71% in the previous quarter. Regarding earnings per share, 69% surpassed market expectations by $0.02 or more, compared to 71% previously.

In contrast, infrastructure software companies have managed to avoid this downward trend, showing robust revenue performance for the second quarter in a row. SolarWinds (SWI) exceeded market expectations by 7.2%, Palantir by 6.6%, MongoDB by 5.6%, and Elastic (ESTC) by 4.5%. Notably, 80% of infrastructure software companies exceeded revenue expectations by more than 1%, and 85% surpassed earnings per share expectations by more than $0.02.

Weiss highlighted Palantir as the second-best performing stock in the infrastructure software sector, despite high expectations. The company has seen accelerated revenue growth for six consecutive quarters, indicating its potential for sustained growth. Palantir’s stock has risen by 22% this year, while the Nasdaq has declined by over 7% during the same period.

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Top 10 Big Data Certifications in 2025 – Analytics Insight

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Big data plays a crucial role in various industries. For professionals looking for career growth, can benefit from certifications that validate expertise. Here are the top 10 big data certifications in 2025.

1. IBM Data Science Professional Certificate

This certificate aids in understanding the basics of data science, machine learning, and data visualization without any previous exposure to data or knowledge.

2. Cloudera CDP Certification Program

Cloudera offers certification to users of the Cloudera Data Platform (CDP). The tests assess both general and administrator mastery.

3. Certified Analytics Professional (CAP)

This certification covers analytics problem framing, model building and data handling. Great for those wanting to polish their expertise in analytics.

4. SAS Certified Data Scientist

SAS offers a comprehensive program that covers machine learning, AI and data curation. It also requires passing multiple exams.

5. Data Science Council of America (DASCA) Certifications

The Data Science Council of America (DASCA) presents different certifications applicable to engineers, analysts and scientists in big data domains. The certification credentials exist at both beginning and advanced stages of professional career levels.

6. MongoDB Professional Certification

MongoDB delivers professional exam programs that validate developers and database administrators who work exclusively with NoSQL database technology. The certifications serve as proof of competence in managing big data projects.

7. Dell EMC Data Scientist Certifications

Dell EMC offers certifications covering data science, big data analytics and data engineering. Practical skills related to advanced analytics form the core content focus of these exams.

8. Microsoft Azure Data Scientist Associate

The certification evaluates skilled individuals who operate Azure Machine Learning as well as Databricks platforms. The certification serves employees who use cloud-based data solutions in their work.

9. Open Certified Data Scientist

The certification program has unique requirements distinct from standard test exams. The assessment requires both documentation of abilities from candidates through written submissions as well as feedback from their peers.

10. Columbia University Data Science Certificate

Columbia University delivers non-degree training for data science core knowledge acquisition. It includes coursework in machine learning and data analysis.

Conclusion

Big data certifications help professionals validate their expertise. They also open doors to better job opportunities. Choosing the right certification depends on career goals and industry requirements.

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GitHub Leverages AI for More Accurate Code Secret Scanning

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MMS Steef-Jan Wiggers

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GitHub has launched an AI-powered secret scanning feature within Copilot, integrated into GitHub Secret Protection, that leverages context analysis to improve the detection of leaked passwords in code significantly. This new approach addresses the shortcomings of traditional regular expression-based methods, which often miss varied password structures and generate numerous false positives.

According to a GitHub blog post detailing the development, the system now analyzes the usage and location of potential secrets to reduce irrelevant alerts and provide more accurate notifications critical to repository security. Sorin Moga, a senior software engineer at Sensis, commented on LinkedIn that this marks a new era in platform security, where AI not only assists in development, but also safeguards code integrity.

A key challenge identified during the private preview of GitHub’s AI-powered secret scanning was its struggle with unconventional file types and structures, highlighting the limitations of relying solely on the large language model’s (LLM) initial training data. GitHub’s initial approach involved “few-shot prompting” with GPT-3.5-Turbo, where the model was provided with examples to guide detection.

To address these early challenges, GitHub significantly enhanced its offline evaluation framework by incorporating feedback from private preview participants to diversify test cases and leveraging the GitHub Code Security team’s evaluation processes to build a more robust data collection pipeline. They even used GPT-4 to generate new test cases based on learnings from existing secret scanning alerts in open-source repositories. This improved evaluation allowed for better measurement of precision (reducing false positives) and recall (reducing false negatives).

GitHub experimented with various techniques to improve detection quality, including trying different LLM models (like GPT-4 as a confirming scanner), repeated prompting (“voting”), and diverse prompting strategies. Ultimately, they collaborated with Microsoft, adopting their MetaReflection technique, a form of offline reinforcement learning that blends Chain of Thought (CoT) and few-shot prompting to enhance precision.

As stated in the GitHub blog post:

We ultimately ended up using a combination of all these techniques and moved Copilot secret scanning into public preview, opening it widely to all GitHub Secret Protection customers.

To further validate these improvements and gain confidence for general availability, GitHub implemented a “mirror testing” framework. This involved testing prompt and filtering changes on a subset of repositories from the public preview. By rescanning these repositories with the latest improvements, GitHub could assess the impact on real alert volumes and false positive resolutions without affecting users.

This testing revealed a significant drop in both detections and false positives, with minimal impact on finding actual passwords, including a 94% reduction in false positives in some cases. The blog post concludes that:

This before-and-after comparison indicated that all the different changes we made during private and public preview led to increased precision without sacrificing recall, and that we were ready to provide a reliable and efficient detection mechanism to all GitHub Secret Protection customers.

The lessons learned during this development include prioritizing accuracy, using diverse test cases based on user feedback, managing resources effectively, and fostering collaboration. These learnings are also being applied to Copilot Autofix. Since the general availability launch, Copilot secret scanning has been part of security configurations, allowing users to manage which repositories are scanned.

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End of the Road for FaunaDB: Is the Future Open Source?

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MMS Renato Losio

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The team behind the distributed serverless database Fauna has recently announced plans to shut down the service by the end of May. While the managed database will be terminated soon and all customers will have to migrate to other platforms, Fauna is committing to releasing an open source version of the core database technology alongside the existing drivers and CLI tooling.

Started in 2011 as FaunaDB by the team that scaled Twitter by building its in-house databases and systems, Fauna tried for many years to combine the power of a relational database with the flexibility of JSON documents. Fauna was designed to scale horizontally within a data center to maximize throughput while easily spanning globally distributed sites, ensuring reliability and local performance. With the vision of enabling “applications without database limits” and claiming use by more than 80,000 development teams, the service has now reached the end of the road.

According to the Fauna Service End of Life FAQ, the Fauna service will be turned off on May 30th, and all Fauna accounts will be deleted. The team writes:

Driving broad based adoption of a new operational database that runs as a service globally is very capital intensive. In the current market environment, our board and investors have determined that it is not possible to raise the capital needed to achieve that goal independently.

Yan Cui, AWS Serverless Hero and serverless expert, writes:

Sad to see Fauna go. They were one of the first truly serverless databases on the market.

Ankur Raina, senior staff sales engineer at Cockroach Labs, summarizes:

The DB market is brutal (…) Getting large customers on Serverless databases is hard. (…) Fauna was trying to build the document model of MongoDB, consistency & geo distribution of CockroachDB but without any ability to run it beyond two cloud providers.

The sunsetting of a once-popular database has sparked many reactions within the community. In a popular Hacker News thread, Pier Bover, founder of Waveki, writes:

A decade ago it seemed that edge computing, serverless, and distributed data was the future. Fauna made a lot of sense in that vision. But in these years since, experimenting with edge stuff, I’ve learned that most data doesn’t really need to be distributed. You don’t need such a sophisticated solution to cache a subset of data for reads in a CDN or some KV. What I’m saying is that, probably, Cloudflare Workers KV and similar services killed Fauna.

User strobe adds:

I found Fauna very interesting from a technical perspective many years ago, but even then, the idea of a fully proprietary cloud database with no reasonable migration options seemed pretty crazy at the time. (…) Hope that something useful will be open sourced as a result.

Peter Zaitsev, open source advocate, questions instead:

While there is no alternative history, I wonder what would have happened if Fauna had chosen to start as Open Source, become 100x more widely adopted but monetize a smaller portion of their customers due to “competing” Open Source alternatives.

The market of distributed databases that once competed with Fauna includes Google Spanner, PlanetScale, CockroachDB, and TiDB, among others. A migration guide is now available, offering the option to create snapshot exports, with the exported data stored as JSON files in an AWS S3 bucket. For smaller collections, data can also be exported using FQL queries.

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Tessell’s Multi-Cloud DBaaS is Now Available on Google Cloud

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Tessell, the leading next-generation, multi-cloud database-as-a-service (DBaaS), is announcing that the Tessell DBaaS is now available in the Google Cloud Marketplace, accompanied by support for Oracle, PostgreSQL, SQL Server, MySQL, MongoDB, and Milvus on all four major cloud platforms—Azure, AWS, Google Cloud, and OCI. With this launch, Tessell empowers enterprises to modernize their transactional applications, database estates, and data architectures all within Google Cloud’s infrastructure. 

This announcement taps into the recent collaboration between Oracle and Google Cloud, which brought support for Oracle databases on Google Cloud infrastructure. Building off of this opportunity for innovation in cloud-based data management, Tessell delivers a fully managed solution for streamlining the complexities of managing multiple data ecosystems at once, according to the company. 

“Tessell’s support for Oracle, PostgreSQL, SQL Server, MySQL, MongoDB, and Milvus on Google Cloud empowers enterprises to capitalize on the newly available opportunity to bring application workloads to Google Cloud GCP,” said Bala Kuchibhotla, co-founder and CEO at Tessell. “Tessell has already seen rapid adoption of its fully managed database service on Google Cloud, with customers successfully running mission-critical workloads. Organizations are leveraging the platform to simplify operations, improve scalability, and accelerate cloud adoption without the complexities traditionally associated with database management. As more enterprises recognize the benefits of this streamlined approach, Tessell looks forward to expanding its footprint and supporting even more businesses in their cloud transformation journey.”

Tessell’s fully managed service offers the following advantages:

  • Automated maintenance, including for patching, backup, and recovery, which helps reduce downtime and improve reliability
  • High availability and disaster recovery with built-in multi-zone availability and cross-region recovery to ensure business continuity 
  • Data security and compliance with adaptable backup options and strong recovery mechanisms that adhere to strict compliance and regulatory policies
  • Enterprise-grade flexibility by enabling the automation and security benefits of PaaS with the customization features of IaaS
  • Unified security and compliance posture, allowing enterprises to extend their existing security and compliance services to Google Cloud while bringing their own keys 

“Bringing Tessell DBaaS to Google Cloud Marketplace will help customers quickly deploy, manage, and grow the managed database service on Google Cloud’s trusted, global infrastructure,” said Dai Vu, managing director, marketplace and ISV GTM programs at Google Cloud. “Tessell can now securely scale and support customers on their digital transformation journeys.”

“Tessell’s deep database expertise, customer-first approach, and solution-focused mindset made our cloud migration seamless,” said Martti Kontula, head of OT and data at Landis+Gyr. “Their ability to optimize and manage database workloads on Google Cloud ensured a smooth transition. The Tessell platform delivers a powerful, intuitive experience, providing full visibility into database health and performance at a glance. For any enterprise seeking to run databases efficiently in the cloud, Tessell is the ideal choice.”

To learn more about Tessell, please visit https://www.tessell.com/.

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Valkey 8.1’s Performance Gains Disrupt In-Memory Databases – The New Stack

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Valkey 8.1’s Performance Gains Disrupt In-Memory Databases – The New Stack


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2025-03-25 06:06:04

Valkey 8.1’s Performance Gains Disrupt In-Memory Databases


Databases

/


Open Source

Redis fork Valkey, with a new multithreading architecture, delivers a threefold improvement in speed and memory efficiency gains.


Mar 25th, 2025 6:06am by


Featued image for: Valkey 8.1’s Performance Gains Disrupt In-Memory Databases

NAPA, Calif — A year ago, Redis announced that it was dumping the open source BSD 3-clause license for its Redis in-memory key-value database and was moving it to a “source-available” Redis Source Available License (RSALv2) and Server Side Public License (SSPLv1).

That move went over like a lead brick with many Redis developers and users. So the disgruntled developers forked a new project, Valkey, as “an open source alternative to the Redis in-memory NoSQL data store.” Now it’s become clear that this has become a remarkably successful fork. 

How successful? According to a Percona research paper, “75% of surveyed Redis users are considering migration due to recent licensing changes. … Of those considering migration, more than 75% are testing, considering, or have adopted Valkey.” Perhaps a more telling point is that third-party Redis developer companies, such as Redisson, are supporting both Redis and Valkey.

Multithreading and Scalability

It’s not just the licensing changes that make Valkey attractive, though. At the Linux Foundation Member SummitMadelyn Olson, a principal software engineer at Amazon Web Services (AWS) and Valkey project maintainer said in her keynote speech that Valkey is far faster thanks to incorporating enhanced multithreading and scalability features. 

That, Olson added, was not the original plan. “We wanted to keep the open source spirit of the Redis project alive, but we also wanted the value to be more than just a fork. We organized a contributor summit in Seattle where we got together developers and users to try to figure out what this new project should look like. At the time, I was really expecting us to just focus on caching, the main workload that Redis open source was serving. What we heard from our users is that they wanted so much more. They wanted Valkey to be a high-performance database for all sorts of distributed workloads. And so although that would add a lot of complexity to the project, the new core team sort of took on that mantle, and we tried to build that for our community.”

They were successful. By August of 2024, Dirk Hohndel, a Linux kernel developer and long-time open source leader, said the Valkey 8.0 redesign of Redis’s single-threaded event loop threading model with a more sophisticated multithreaded approach to I/O operations had given him “roughly a threefold improvement in performance, and I stream a lot of data, 60 million data points a day.” In addition, with Valkey 8, he saw about a “20% reduction in the size of separate cache tables. When you’re talking about terabytes and more on Amazon Web Services, that’s a real savings in size and cash.”

Shifting back to the current day, Olson added, “Over the last couple of months, we’ve been dramatically improving the core engine by adding Rust into the core to add memory safety. We’ve been changing the internal algorithm for how the cluster mode works to improve reliability and improve the failover times. We’re also dramatically changing how the internal data structures work since they were based on 10-year-old pieces of software, so they can better take advantage of modern hardware.”

In addition, the developer team has rebuilt the key-value store from scratch to take better advantage of modern hardware based on the work done at Google on the so-called Swiss Tables. Olson continued, “In just a few short weeks, we’ll release these improvements as part of Valkey 8.1 just one year after the project’s anniversary.” This new release includes up to 20% memory efficiency improvements, the most common bottleneck within caching systems, and state-of-the-art data structures.

Looking ahead, Valkey plans to introduce more multithreaded performance improvements, a highly scalable clustering system, and new core changes to data types. Does that sound good to you? The project remains open to new contributors and invites interested parties to join via GitHub

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