DocumentDB: A New Open Source Option Challenging Database Lock-In & Powering the AI Revolution
The database landscape is shifting. Enterprises are increasingly seeking alternatives to proprietary solutions,especially as the demands of artificial Intelligence (AI) workloads surge. Now,a new open-source DocumentDB project,backed by AWS,Microsoft,and the Linux Foundation,is poised to disrupt the status quo. This article dives deep into what this means for your data strategy, offering a thorough look at the technology, its benefits, and how to evaluate it for your organization.The Rise of Document Databases & the Need for Choice
Document databases are gaining traction as of their flexibility and ability to handle diverse, semi-structured data - a perfect fit for modern applications, particularly those driving AI. However, traditionally, options have been limited, often leading to vendor lock-in and escalating costs. This new DocumentDB project directly addresses these concerns. As Rajeev Gupta, Manager of Product Management at AWS, explained to venturebeat, it offers a compelling option.While Amazon DocumentDB remains a robust, proprietary option, this open-source initiative provides a different path. Here’s the key difference: The Linux Foundation project leverages an open-source engine built on top of PostgreSQL, unlike Amazon DocumentDB’s unique engine.AWS & Microsoft: A Collaborative Approach
AWS isn’t abandoning its existing DocumentDB service. Instead, they’re taking a dual-track approach, mirroring their strategy with OpenSearch Service and community OpenSearch. Gupta confirmed AWS will actively contribute innovations from amazon DocumentDB to the open-source project and integrate features from the open-source version back into their managed service. Microsoft is equally invested. They’re contributing substantially to the project’s AI capabilities,specifically integrating microsoft Research’s DiskANN vector indexing algorithms and semantic operators – originally developed for PostgreSQL’s AI features. As Dima Gavrylyuk of Microsoft stated, they are prioritizing AI investments across both DocumentDB and the broader PostgreSQL ecosystem.Why This Matters for AI Workloads
The timing of this launch isn’t accidental. AI applications are hungry for data, and vector databases are becoming crucial for tasks like semantic search and advice engines. This new DocumentDB project offers several advantages for AI: Competitive Edge: The inclusion of DiskANN provides immediate performance benefits for AI workloads. Cost Savings: Avoiding proprietary licensing fees can significantly reduce expenses for data-intensive AI applications. Rapid Innovation: The open-source nature fosters community contributions and faster growth of new AI features.What Does This Mean for
Your Enterprise? This isn’t just a technical development; it’s a strategic possibility for enterprise data teams. Here’s how you can benefit: Reduce Vendor Dependence: DocumentDB provides a viable alternative to proprietary databases, giving you more control over your data infrastructure. Mitigate Lock-In Risk: Architecting new AI applications around DocumentDB from the start avoids potential lock-in with closed-source technologies. Leverage PostgreSQL’s Reliability: Benefit from the proven enterprise-grade reliability and extensive ecosystem of PostgreSQL. Strategic Evaluation: Begin testing DocumentDB in development environments to assess migration complexity for your* specific workloads. Here’s a quick guide to help you get started:- Assess Your Needs: Identify workloads that coudl benefit from a document database.
- Explore Compatibility: Determine how easily your existing applications can integrate with DocumentDB.
- Pilot Project: Start with a small-scale pilot project to evaluate performance and scalability.
- Consider Migration: Develop a migration plan if you decide to adopt DocumentDB for production workloads.
A Future of Open Innovation in Databases
The launch of this open-source DocumentDB project signals a broader trend towards open innovation in the database world. It empowers enterprises with more choice, reduces reliance on single vendors, and accelerates the development of cutting-edge database capabilities – particularly for the demanding requirements of AI.For IT leaders looking to future-proof their data strategy, DocumentDB deserves serious consideration. It’s not just a database; it’s a strategic hedge against vendor lock-in and a gateway to the next generation of AI-powered applications.Daily insights on business use cases with VB Daily
Document databases are an increasingly important type of technology in the gen AI era.
A document database is a type of NoSQL database that doesn’t rely on rows and columns like a conventional relational database, instead it uses the JSON (JavaScript Object Notation) format. There are multiple vendors that develop document databases including mongodb, which now has a proprietary closed source technology. In an effort to open up the market, Microsoft began developing its own document database known as documentdb and made it open source in January of this year. This week,DocumentDB is moving to the Linux Foundation where it has also gained the backing of Microsoft’s cloud rivals AWS and Google.
The move creates the first vendor-neutral open source alternative to MongoDB that has the potential to save enterprises money, while also eliminating database vendor lock-in. Document databases are important for AI apps for tasks such as chats, context and memory.
“AI apps are all about semi-structured data and document databases are purpose built for it,” Kirill Gavrylyuk, vice president at Microsoft and DocumentDB’s primary architect, told VentureBeat “But there is no open source standard engine for document databases, like what PostgreSQL is for relational databases.”
DocumentDB: A New Open Source option Challenging Database Lock-In & Powering the AI Revolution
The database landscape is shifting. Enterprises are increasingly seeking alternatives to proprietary solutions, especially as the demands of Artificial Intelligence (AI) workloads surge. Now, a new open-source DocumentDB project, backed by AWS, Microsoft, and the Linux foundation, is poised to disrupt the status quo.This article dives deep into what this means for your data strategy, offering a comprehensive look at the technology, its benefits, and how to evaluate it for your organization.The Rise of Document Databases & the Need for Choice
Document databases are gaining traction as of their flexibility and ability to handle diverse, semi-structured data – a perfect fit for modern applications, particularly those driving AI. However, traditionally, options have been limited, often leading to vendor lock-in and escalating costs. This new DocumentDB project directly addresses these concerns. As Rajeev Gupta, Manager of Product Management at AWS, explained to venturebeat, it offers a compelling alternative. While Amazon DocumentDB remains a robust, proprietary option, this open-source initiative provides a different path. Here’s the key difference: The Linux Foundation project leverages an open-source engine built on top of PostgreSQL, unlike Amazon DocumentDB’s unique engine.AWS & Microsoft: A Collaborative Approach
AWS isn’t abandoning its existing DocumentDB service. Instead, Gupta emphasized a commitment to investing in both Amazon DocumentDB and the open-source version, mirroring their approach with OpenSearch Service and the community OpenSearch project. The plan is to create a two-way street: Contributions to Open Source: AWS will contribute innovations from Amazon DocumentDB to the open-source project. Adoption of Open Source Features: AWS will integrate valuable features and capabilities from the open-source DocumentDB engine into its managed Amazon DocumentDB service. This collaborative strategy, coupled with critically important investment from Microsoft, signals a serious commitment to the project’s success. Microsoft is particularly focused on integrating AI capabilities, leveraging its research in areas like vector indexing.AI Workloads: the catalyst for Change
The timing of this launch isn’t accidental.The demand for document databases is being driven by the explosion of AI applications. These applications require databases capable of handling complex data structures and performing advanced analytics. the open-source DocumentDB project already boasts a significant advantage in this area: integration of Microsoft Research’s DiskANN (Disk Approximate Nearest Neighbor) vector indexing algorithms. developed for PostgreSQL’s AI capabilities, DiskANN enables faster and more efficient similarity searches – crucial for AI tasks like image recognition and natural language processing. This integration provides immediate competitive advantages, and avoids the perhaps high licensing costs associated with proprietary alternatives. As Oleksandr Gavrylyuk noted, Microsoft is heavily investing in open-source AI contributions, prioritizing the AI capabilities of DocumentDB and the broader PostgreSQL ecosystem.What Does This Mean for Your Enterprise?
This new DocumentDB project presents a strategic opportunity for enterprise data teams. here’s a breakdown of the key implications: Reduce Vendor Dependence: DocumentDB offers a powerful hedge against being locked into a single vendor’s proprietary technology. Avoid Lock-In for New AI Applications: If you’re building new AI applications,you can architect them around DocumentDB from the start,avoiding potential lock-in while benefiting from PostgreSQL’s reliability. Access Cutting-Edge Capabilities: Gain access to state-of-the-art document database features without the risks traditionally associated with database strategy decisions. Strategic Evaluation: You should begin evaluating DocumentDB in development environments to assess migration complexity for your specific workloads. Here’s a quick checklist for evaluating DocumentDB:- Identify potential use cases: Where could a document database improve your application performance or flexibility?
- Assess migration complexity: How challenging would it be to migrate your existing data to DocumentDB?
- Evaluate AI workload requirements: Do your AI applications require vector indexing or other advanced features?
- Consider long-term costs: Compare the total cost of ownership (TCO) of DocumentDB versus proprietary alternatives.
The Future of Document Databases is Open
The launch of this open-source DocumentDB project marks a significant turning pointDocumentDB: A New Open Source Option Challenging Database Lock-In & Powering the AI Revolution
The database landscape is shifting. Enterprises are increasingly seeking alternatives to proprietary solutions, especially as the demands of Artificial Intelligence (AI) workloads surge. Now, a new open-source DocumentDB project, backed by AWS, Microsoft, and the linux Foundation, is poised to disrupt the status quo. This article dives deep into what this means for your data strategy, offering a comprehensive look at the technology, its benefits, and how to evaluate it for your organization.The Rise of Document Databases & the Need for Choice
document databases are gaining traction because of their flexibility and scalability – crucial for modern applications. though, many existing options come with vendor lock-in, potentially limiting your options and increasing costs. This new DocumentDB project directly addresses this concern, offering a compelling alternative. As Neal Gupta, Manager of Product Management at AWS, explained to VentureBeat, the project is MongoDB compatible but fundamentally different from Amazon DocumentDB. While Amazon documentdb utilizes a proprietary engine, this new initiative leverages an open-source engine built as an extension on the robust PostgreSQL database.AWS’s Commitment: Open Source & innovation
AWS isn’t just participating; they’re committed to driving this project forward. Gupta emphasized that AWS will continue investing in both Amazon documentdb and the open-source DocumentDB, mirroring their approach with OpenSearch Service and the community OpenSearch project. Here’s what you can expect: Contribution: AWS will contribute innovations from Amazon DocumentDB to the open-source project. Adoption: AWS will integrate features and capabilities from the open-source DocumentDB engine into its managed Amazon DocumentDB service over time. Dual Path: A commitment to fostering both proprietary and open-source development.AI Workloads: The Catalyst for Change
The timing of this project isn’t accidental. The explosion of AI applications is creating an urgent need for databases capable of handling complex, data-intensive workloads. Document databases are particularly well-suited for this purpose. This new DocumentDB already boasts significant advantages in this area: DiskANN integration: It incorporates Microsoft research’s DiskANN (Disk Approximate Nearest Neighbor) vector indexing algorithms. Semantic Operators: leverages semantic operators developed for PostgreSQL’s AI capabilities. Cost-effectiveness: Avoids the potentially high licensing costs associated with proprietary alternatives. As stated by Gavrylyuk, microsoft is heavily investing in open-source AI contributions, prioritizing both DocumentDB and the broader PostgreSQL ecosystem.What Does This Mean for Your Enterprise?
This development has significant implications for enterprise data teams. Here’s a breakdown of how it impacts different scenarios: reducing Vendor Dependence: DocumentDB provides a strategic hedge against being locked into a single vendor’s technology. It empowers you with more control over your data infrastructure. New AI Application Development: Architect new AI applications around DocumentDB from the start to avoid potential lock-in while benefiting from PostgreSQL’s reliability and ecosystem. Migration Evaluation: Begin evaluating DocumentDB in development environments to assess the complexity of migrating existing workloads. Understanding this upfront will save you time and resources. Cutting-edge Capabilities: Gain access to state-of-the-art document database features without the risks traditionally associated with database strategy decisions. Here’s a quick checklist for IT leaders:- Assess your current database landscape. Identify potential areas where DocumentDB could offer benefits.
- Start a proof-of-concept. Experiment with DocumentDB in a non-production environment.
- Evaluate migration complexity. Understand the effort required to move existing workloads.
- Monitor the project’s development. Stay informed about new features and capabilities.
The Future of Document Databases is Open
The emergence of this open-source DocumentDB project signals a significant shift in the database market. It’s a powerful option for organizations seeking flexibility,cost-effectiveness,and a future-proof data strategy,particularly as AI continues to reshape the technological landscape. By embracing this open-source alternative, you can unlock new possibilities and avoid the pitfalls of proprietary lock-in.**Daily insights on business
DocumentDB: A New Open source Option Challenging Database Lock-In & Powering the AI Revolution
The database landscape is shifting. Enterprises are increasingly seeking alternatives to proprietary solutions, especially as the demands of Artificial Intelligence (AI) workloads surge. Now, a new open-source DocumentDB project, backed by AWS, Microsoft, and the Linux Foundation, is poised to disrupt the market – offering a compelling alternative to both Amazon’s DocumentDB and other established players. Let’s break down what this means for you and your organization.The Rise of Document Databases & the Need for Choice
Document databases are gaining traction because of their flexibility and ability to handle the complex, evolving data structures common in modern applications. This demand is being accelerated by AI. AI applications require efficient storage and retrieval of unstructured and semi-structured data – a sweet spot for document databases. However,reliance on single-vendor,closed-source solutions can lead to vendor lock-in,escalating costs,and limited control. This is where the new DocumentDB project steps in.Understanding the Players: AWS, Microsoft, and the Linux Foundation
Amazon Web Services (AWS) already offers Amazon DocumentDB, a fully managed document database service compatible with MongoDB. But this new project takes a different approach. As explained by AWS’s manager of Product Management, the Linux Foundation project, while also mongodb compatible, is built as an extension on top of PostgreSQL – a robust and widely-used open-source relational database. This differs significantly from the engine powering Amazon DocumentDB. AWS isn’t abandoning its existing service. They plan to continue investing in both Amazon DocumentDB and the open-source version, mirroring their strategy with OpenSearch Service and the community OpenSearch project. Importantly, AWS intends to contribute innovations from Amazon DocumentDB to the open-source project and, reciprocally, adopt features from the open-source engine into their managed service.AI Workloads: The Catalyst for Change
The timing of this project isn’t accidental. The explosion of AI applications is driving a critical need for database solutions that can handle the unique demands of these workloads. The open-source DocumentDB project is already integrating cutting-edge AI capabilities,including: Microsoft Research’s DiskANN: This provides efficient vector indexing algorithms,crucial for similarity searches in AI applications. Semantic Operators for PostgreSQL: Leveraging PostgreSQL’s growing AI functionality. This combination delivers immediate competitive advantages for AI workloads without the potentially high licensing costs associated with proprietary alternatives. Microsoft is heavily invested in open-source AI contributions, and DocumentDB is a key part of that strategy.What Does This Mean for Your Enterprise?
This new DocumentDB project presents significant opportunities for enterprise data teams. Here’s a breakdown: Reduce Vendor Dependence: DocumentDB offers a strategic alternative to avoid being locked into a single vendor’s ecosystem. You gain more control over your data infrastructure. Mitigate Risk: By diversifying your database options, you reduce the risk associated with proprietary technology changes or price increases. Accelerate AI Innovation: Access cutting-edge document database capabilities specifically designed for AI workloads. New Application Architectures: If you’re building new AI applications, you can architect around DocumentDB from the start, avoiding lock-in altogether. proven Reliability: Benefit from the proven enterprise reliability and extensive ecosystem of postgresql. Here’s a quick action plan:- Evaluate in development: Begin testing DocumentDB in your development environments to assess migration complexity for your specific workloads.
- Consider for New Projects: For new AI applications, seriously consider DocumentDB as your foundational database.
- Stay Informed: Keep abreast of the project’s development and feature releases.
A Future of Open, Powerful document Databases
the emergence of this open-source DocumentDB project signals a significant shift in the database landscape. It empowers enterprises with greater choice, reduces vendor lock-in, and unlocks the potential of AI-powered applications. By embracing this new option, you* can position your organization for success in the rapidly evolving world of data and artificial intelligence.Daily insights on business use cases with VB Daily If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from
DocumentDB: A New Open Source Option challenging Database Lock-In & Powering the AI Revolution
The database landscape is shifting. Enterprises are increasingly seeking alternatives to proprietary solutions, especially as the demands of Artificial Intelligence (AI) workloads surge. Now, a new open-source DocumentDB project, backed by AWS and Microsoft, is poised to disrupt the status quo, offering a compelling alternative to both Amazon’s own DocumentDB and other established players. Let’s break down what this means for you and your organization.The Rise of Document Databases & the Need for Choice
Document databases are gaining traction as of their flexibility and ability to handle the complex, evolving data structures common in modern applications. This demand is being accelerated by AI. AI applications require efficient storage and retrieval of unstructured and semi-structured data – a sweet spot for document databases. Though, reliance on single-vendor, closed-source solutions can lead to vendor lock-in and escalating costs. This is where the new open-source DocumentDB project steps in.Understanding the Players: AWS, Microsoft, and the Linux Foundation
Amazon Web Services (AWS) already offers Amazon DocumentDB, a fully managed document database service.But it’s important to understand the difference between this and the new open-source initiative. As explained by AWS’s Manager of Product Management,the open-source project,spearheaded by the Linux Foundation,is built as an extension on top of PostgreSQL. This contrasts with Amazon DocumentDB’s unique engine. Here’s the key takeaway: AWS isn’t abandoning its existing DocumentDB service. Instead, they’re committing to a dual-path strategy. They will continue to invest in both Amazon DocumentDB and contribute to the open-source project, mirroring their approach with OpenSearch Service and the community OpenSearch.Expect to see innovations flow in both directions.AI Workloads: The catalyst for Change
The timing of this project isn’t accidental. AI workloads are driving an urgent need for scalable, cost-effective database solutions. The open-source DocumentDB project is already equipped with powerful AI capabilities, thanks to the integration of: Microsoft Research’s diskann: This provides efficient vector indexing algorithms, crucial for similarity searches in AI applications. Semantic Operators for PostgreSQL: these enhance PostgreSQL’s AI functionality, bringing advanced capabilities to DocumentDB. This combination delivers immediate competitive advantages for AI-powered applications, without the potentially high licensing costs associated with proprietary alternatives. Microsoft is heavily invested in open-source AI and is prioritizing these capabilities within both DocumentDB and the broader PostgreSQL ecosystem.What Does This Mean for Your Enterprise?
this development has significant implications for enterprise data teams. Here’s a breakdown: Reduce Vendor Dependence: DocumentDB offers a strategic alternative, mitigating the risks of being locked into a single vendor’s technology. avoid Lock-In for New AI Applications: If you’re building new AI applications, architecting around DocumentDB from the start allows you to avoid proprietary lock-in while benefiting from PostgreSQL’s reliability and extensive ecosystem. Strategic Evaluation: begin evaluating documentdb in your development environments now to assess migration complexity for your existing workloads. Cutting-edge Capabilities: Gain access to state-of-the-art document database features without the risks traditionally associated with database strategy. Here’s a quick checklist for IT leaders:- Assess your current database landscape. Identify potential workloads that could benefit from a document database.
- Explore DocumentDB’s documentation and resources. Understand its capabilities and compatibility with your existing systems.
- Start a proof-of-concept project. Test DocumentDB with a representative workload to evaluate its performance and suitability.
- Consider long-term implications. Factor in the benefits of open-source flexibility and community support.
The Future is Open: Empowering Innovation
The emergence of this open-source DocumentDB project signals a broader trend towards greater choice and control in the database market. By embracing open standards and fostering collaboration, AWS and Microsoft are empowering enterprises to build more flexible, scalable, and cost-effective data solutions – especially for the demanding requirements of the AI era. Don’t just react to the changing database landscape; proactively explore the opportunities DocumentDB presents. your future data strategy may depend on itDelivering the promise of open source document database at the Linux Foundation
Microsoft initially launched the open-source documentdb project in January of 2025.
The project was hosted within the Microsoft org on GitHub and had been generating broad industry interest over the course of the year. Having an open-source project isn’t just about code or licensing, it’s also about contributions and community.
“Under the Linux Foundation’s governance, DocumentDB will benefit from vendor neutrality and broader collaboration,” Gavrylyuk said.
Microsoft isn’t just dumping code either. Gavrylyuk emphasized that Microsoft will continue to invest heavily in the project and will continue to have strong portrayal in the Technical Steering Committee to help shape the vision and roadmap of the project.
“By joining the Linux Foundation, a neutral foundation, we are aiming to be more inviting to the developer community to contribute and shape the direction of the project,” Gavrylyuk said. “Moreover, through the Linux Foundation, we want to provide an assurance to the developer community that this project is here to stay, open source, and will continue to move forward.”
What’s inside documentdb and why it matters for enterprise data professionals
Aside from its open-source nature, there is another critical element that makes the database particularly attractive to enterprises. Instead of being an entirely new database technology, it’s based on the open-source PostgreSQL database.
PostgreSQL has emerged to become one of the most widely deployed open source databases of all time and has newfound adoption in the AI era. DocumentDB includes a PostgreSQL extension that brings first class BSON (Binary JSON) datatype support to PostgreSQL. It also integrates an extension that adds document style queries support to PostgreSQL and index management. The PostgreSQL base means that enterprises can benefit from PostgreSQL’s mature ecosystem of tools, monitoring systems and backup solutions. The PostgreSQL foundation also provides ACID (Atomicity, Consistency, isolation and Durability) compliance and proven replication capabilities that address enterprise concerns about data consistency.
DocumentDB also has a gateway that makes the database compatible with open source MongoDB drivers for any language. Gavrylyuk noted that Document DB doesn’t yet have full compatibility with everything in MongoDB, but there is more work to come.
“full compatibility with MongoDB drivers is a critical goal of the project as reflected in the Linux Foundation DocumentDB charter,” he said. “This coupled with the true open source vendor neutral governance of the project will help the broader document database ecosystem thrive, benefitting everybody in the ecosystem, including MongoDB Inc.”
Just to be clear, Amazon DocumentDB isn’t the same thing
While Amazon is among the backers of the new Linux Foundation DocumentDB project, it actually already has its own DocumentDB database.
The Amazon DocumentDB database predates the Microsoft-led technology, having been first announced in 2019. Amazon DocumentDB recently debuted a serveless service that aims to accelerate agentic AI.
While the DocumentDB project, stewarded by Linux Foundation, has a similar name to Amazon DocumentDB, it uses different software under the hood.
“Amazon DocumentDB is a MongoDB API-compatible document database built by AWS,” Rashim Gupta, Sr. Manager,Product Management at AWS,told VentureBeat. “The Linux Foundation project,conversely,while also being MongoDB compatible,uses an open source engine that is built as an extension on PostgreSQL. this is a different engine than the one used in Amazon DocumentDB.”
Gupta noted that AWS will continue to invest in both Amazon DocumentDB and open source DocumentDB akin to how it invests in Amazon OpenSearch Service and community OpenSearch. Moving forward, he said that AWS will start contributing Amazon DocumentDB innovations to the open source project and adopt features and capabilities from the open source DocumentDB engine to its managed Amazon DocumentDB service over time.
AI workloads drive urgent need for database alternatives
The timing reflects growing enterprise demand for document databases to power AI applications.
The project already incorporates Microsoft Research’s DiskANN (Disk approximate Nearest Neighbor) vector indexing algorithms and semantic operators developed for PostgreSQL’s AI capabilities.
This gives DocumentDB immediate competitive advantages for AI workloads while avoiding the licensing costs that can potentially make proprietary alternatives expensive for data-intensive applications.
“Microsoft heavily invests in open source AI contributions across the board,” Gavrylyuk said. “We are investing in the AI capabilities of DocumentDB and also the broader PostgreSQL ecosystem with priority.”
What it means for enterprise data teams
For enterprises looking to reduce database vendor dependence, DocumentDB provides a strategic hedge against potential closed source proprietary technology. IT leaders should begin evaluating DocumentDB in development environments to understand migration complexity for their specific workloads.
Organizations building new AI applications have the opportunity to architect around DocumentDB from the start, avoiding potential closed-source technology lock-in entirely while gaining PostgreSQL’s proven enterprise reliability and ecosystem benefits.
For enterprises looking to lead the way in AI, this news means access to cutting-edge document database capabilities without the vendor lock-in risks that have historically constrained database strategy decisions.
