{"id":11097,"date":"2025-11-18T08:00:19","date_gmt":"2025-11-18T16:00:19","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/cosmosdb\/?p=11097"},"modified":"2025-11-14T09:23:18","modified_gmt":"2025-11-14T17:23:18","slug":"cosmos-db-fabric-mirroring-ga","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/cosmosdb\/cosmos-db-fabric-mirroring-ga\/","title":{"rendered":"Announcing: GA of Cosmos DB in Microsoft Fabric and Cosmos Mirroring"},"content":{"rendered":"

We\u2019re\u00a0excited to announce that Cosmos DB in Microsoft Fabric\u00a0and Cosmos DB Mirroring\u00a0are\u00a0now Generally\u00a0Available, uniting\u00a0your operational and analytical data\u00a0in\u00a0one platform. You can now analyze live Cosmos DB data directly in Fabric\u2014no complex\u00a0or costly\u00a0ETL\u00a0required. Data\u00a0stays\u00a0in sync\u00a0in OneLake, providing\u00a0a single source\u00a0of truth for\u00a0real-time and historical insights.\u00a0Write queries using T-SQL from a SQL Endpoint\u00a0or use Python and Spark\u00a0Notebooks in Fabric.\u00a0<\/span>\u00a0<\/span><\/p>\n

As a distributed NoSQL\u00a0database\u00a0Cosmos DB in Fabric brings\u00a0support for semi or unstructured data to\u00a0analytics\u00a0and ML\u00a0workloads\u00a0as well as\u00a0a host of\u00a0additional\u00a0new capabilities to Fabric, including vector indexing and search using DiskANN\u00a0and reverse ETL capabilities allowing customers to serve analytics to users with incredible speed at massive scale.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Cosmos<\/a><\/p>\n

Whether\u00a0you\u2019re\u00a0building dashboards, running analytics, or training ML models, you can work on fresh operational data for faster, AI-ready insights. This GA release delivers production-grade performance, enterprise security, and the scale of Cosmos DB\u2019s low-latency architecture within the unified Fabric experience.\u00a0Let\u2019s\u00a0go into some of\u00a0these benefits and how you can use\u00a0Cosmos DB in Fabric\u00a0in your workloads.<\/span>\u00a0<\/span><\/p>\n

Cosmos DB in Fabric has been a home run for Kinectify. As a company, we store a lot of data in Cosmos DB, and being able to automatically, reliably and performantly move data with zero ETL into Fabric has allowed us to experiment with Fabric in ways that we simply would not have been able to if we had to setup the ETL ourselves.<\/p>\n

Mike Calvin, CTO at Kinectify<\/p><\/blockquote>\n

Vector indexing support\u00a0for AI\u00a0and ML workloads<\/h2>\n

Cosmos DB in Microsoft Fabric is an AI-optimized NoSQL database and is the first database in Azure to offer DiskANN<\/a>, a graph-based indexing and search system that can index, store, and search large sets of vector data on relatively\u00a0small amounts\u00a0of computational resources. DiskANN\u00a0provides fast and\u00a0efficient query filtering via pushdown to the index to enable fast and cost-effective hybrid queries.\u00a0It also has support for full-text indexing\u00a0and search\u00a0with\u00a0BM25<\/a>\u00a0as well as hybrid search capability that combines vector search with full-text search scoring by using the Reciprocal Rank Fusion (RRF)<\/a> function.<\/span>\u00a0<\/span><\/p>\n

\"Cosmos<\/a><\/p>\n

Cosmos DB in Fabric vector indexing enables efficient similarity searches across high-dimensional data, which is\u00a0also beneficial for data science scenarios including:<\/span>\u00a0<\/span><\/p>\n