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Microsoft is bringing much more database choices into the Microsoft Cloth fold, alongside a collection of initiatives that goal to assist deal with enterprise information complexity.
For actually generations of databases, compute and storage had been at all times tightly coupled. That triggered every kind of scalability and information silo points for enterprises. In 2023, Microsoft Cloth was first launched as a technique to assist overcome that problem. The fundamental thought behind Microsoft Cloth is to be a standard information layer throughout Microsoft’s information and analytics instruments. In November 2024, Microsoft Cloth expanded with help for the Azure SQL transactional database platform.
Microsoft, identical to its rivals at Google at Amazon, has a number of totally different database platforms. Whereas Azure SQL is broadly used, in terms of AI there may be one other extra influential database platform and that’s CosmosDB. On the Construct 2025 convention right now, Microsoft is saying that CosmosDB is lastly coming to Microsoft Cloth. CosmosDB is among the many most crucial databases in use right now for AI as it’s the database that’s on the basis for OpenAI’s ChatGPT service. CosmosDB can be getting a lift by way of integration with Azure AI Foundry, giving extra direct entry for agentic AI to information.
There are additionally a collection of further information updates together with help for Microsoft Copilot within the PowerBI enterprise intelligence platform. SQL Server 2025 database is being previewed and the DiskANN (Disk Approximate Nearest Neighbor) vector index is being open sourced.
These improvements immediately tackle the combination complexity that plagues enterprise information groups when constructing AI functions. A key focus is to eradicate the info fragmentation that hampers enterprise AI initiatives.
“After I speak to clients, the message I persistently get is, please unify, I’m Chief Info Officer, I don’t wish to be the Chief Integration Officer serving to translate AI into my aggressive benefit,” Arun Ulag, Company Vice President for Azure Knowledge at Microsoft, informed VentureBeat.
Cloth accelerates enterprise AI by eliminating information silos
Microsoft Cloth, the corporate’s unified information platform, continues its fast progress trajectory by bringing beforehand separate merchandise collectively in a cohesive ecosystem.
“We’re bringing all of our merchandise collectively and unifying them right into a single product, which is Microsoft Cloth,” Ulag mentioned. “In some methods, you may take into consideration Cloth as virtually like what we did with Workplace 30 years in the past.”
This technique has clearly resonated with enterprises. Ulag mentioned that Microsoft Cloth now has over 21,000 organizations as paying clients worldwide, together with 70% of the Fortune 500.
“It’s rising very, in a short time,” he mentioned.
CosmosDB in Cloth eliminates NoSQL infrastructure overhead
The headline addition to Cloth is CosmosDB, Microsoft’s NoSQL doc database that powers many high-profile AI functions.
“CosmosDB is, by far, usually changing into the database of selection for the world’s AI workloads,” Ulag mentioned. “ChatGPT itself is constructed on CosmosDB… Walmart’s e-commerce retailer runs on CosmosDB as nicely.”
By bringing CosmosDB into Cloth, Microsoft allows organizations to deploy NoSQL databases with out managing advanced infrastructure. A key problem of getting a disaggregated compute and storage method is sustaining efficiency with out latency.
Microsoft has taken very particular technical steps to take care of efficiency via an modern caching system.
“Inside Cloth, we preserve a extremely performant cache, which handles all of the quick updates that CosmosDB does,” Ulag defined. “We now have a really quick synchronization mechanism that’s fully clear to the shopper, the place the info is replicated in close to real-time into OneLake.”
This method delivers millisecond response instances required for AI functions whereas eliminating infrastructure administration duties.
Why open supply information codecs are key to Cloth’s success
Whereas Microsoft connects all its information merchandise via the Cloth technique, OneLake know-how truly shops the info.
There may be large complexity in having a unified information lake that handles a number of totally different information varieties and codecs from SQL, NoSQL and unstructured information. It’s a problem that Microsoft is fixing with an open supply method.
“Microsoft has fully embraced open supply information codecs, so all the pieces in Cloth, no matter whether or not which workload it’s, by default, is at all times in Apache Parquet and Delta Lake,” Ulag mentioned.”It’s actually a unified product, with the unified structure and a unified enterprise mannequin, with all the information sitting in a world SaaS information lake, which is OneLake in open supply information codecs.”
This optimization means all Cloth providers, from SQL to Energy BI to CosmosDB, can entry the identical underlying information with out conversion or duplication, eliminating the standard efficiency penalty related to open codecs.
DiskANN open supply launch brings enterprise-grade vector search to all
Microsoft isn’t simply utilizing open supply for information codecs, it’s additionally contributing its personal code too.
At Construct, Microsoft is saying that it’s open sourcing the DiskANN vector search know-how. Microsoft’s determination to open supply DiskANN represents a big contribution to the AI ecosystem, making enterprise-grade vector search capabilities accessible to all builders.
“We now have a really, very sturdy vector functionality referred to as DiskANN, it was initially created in Microsoft Analysis, and it’s utilized in Bing… constructed into CosmosDB and constructed into Cloth,” mentioned Ulag.
DiskANN implements approximate nearest neighbor (ANN) search algorithms optimized for disk-based operations, making it ultimate for large-scale vector databases that exceed reminiscence limitations. By open sourcing DiskANN, Microsoft allows builders to implement the identical high-performance vector search utilized by ChatGPT and different main AI functions. This helps tackle one of many key challenges in constructing retrieval-augmented technology (RAG) techniques, the place discovering semantically related content material rapidly is important for grounding AI responses in enterprise information.
“We’re permitting everyone to have the ability to get the advantages of the vector retailer that we’re utilizing internally,” Ulag mentioned.
Why it issues for enterprise information leaders
For enterprises main in AI adoption, these bulletins allow extra refined functions that seamlessly combine a number of information varieties.
The complexity and the challenges of coping with information silos aren’t nearly totally different areas however totally different codecs too. The continued evolution of Microsoft Cloth immediately addresses that concern in a approach that no different hyperscaler is doing right now.
The main target and dedication to open supply requirements on the core can be necessary for enterprises because it removes some lock-in danger that may be current if the info was caught in proprietary codecs.
As enterprises more and more compete on AI capabilities, Microsoft’s unified method removes a big barrier to innovation. Organizations that embrace this integration can shift their focus from sustaining advanced information pipelines to creating AI functions that ship tangible enterprise worth—probably outpacing rivals nonetheless scuffling with fragmented architectures.
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