Azure Cosmos DB with DiskANN
The universe's most scalable vector database!
We are excited to announce that native vector indexing and search in Azure Cosmos DB for NoSQL is now available in preview! Azure Cosmos DB is the world’s first full-featured serverless database with vector search and features multiple vector index options from flat (exact), quantized flat, and a new DiskANN-based index. DiskANN is a suite of highly scalable, accurate, and cost-effective approximate nearest neighbor (ANN) algorithms, developed at Microsoft Research, for low-latency and cost-effective vector search at any scale.
You can take advantage of Azure Cosmos DB’s rich features such as a NoSQL query syntax to combine vector search with query filters that can increase the relevancy and accuracy of your vectors searches. You’ll also get all the benefits of Azure Cosmos DB’s flexibility, instant autoscale, 99.999% SLA, geo-replication, and more! Store your data and vectors together, eliminating the need to store vectors in a separate vector database and realize improved consistency, synchronization between vectors and data, and a reduction in the complexity and costs of AI applications.
Read the full blog post: Introducing vector database capabilities in Azure Cosmos DB for NoSQL (Public Preview) - https://devblogs.microsoft.com/cosmos...
#azurecosmosdb #azurecosmosdbconf #ai
Links:
Try Azure Cosmos DB Free: https://aka.ms/trycosmosdb
Microsoft Developers AI Learning Hackathon: https://aka.ms/azurecosmosdbhackathon
Try Azure Cosmos DB free with Azure AI Advantage: https://aka.ms/AzureAIAdvantage
Subscribe to Azure Cosmos DB on YouTube: / azurecosmosdb
Follow Azure Cosmos DB on X: / azurecosmosdb
Follow Azure Cosmos DB on LinkedIn: / azure-cosmos-db
Watch video Azure Cosmos DB with DiskANN online without registration, duration hours minute second in high quality. This video was added by user Azure Cosmos DB 21 May 2024, don't forget to share it with your friends and acquaintances, it has been viewed on our site 1,06 once and liked it 1 people.