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MongoDB Introduces Embedding and Reranking API on Atlas
MongoDB has recently announced the public preview of its Embedding and Reranking API on MongoDB Atlas. The new API gives developers direct access to Voyage AI’s search models within the managed cloud database, enabling them to create features such as semantic search and AI-powered assistants within a single integrated environment, with consolidated monitoring and billing.
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Swiggy Rolls out Hermes V3: from Text-to-SQL to Conversational AI
Swiggy has released Hermes V3, a GenAI-powered text-to-SQL assistant that enables employees to query data in plain English. The Slack-native system combines vector retrieval, conversational memory, agentic orchestration, and explainability to improve SQL accuracy and support multi-turn analytical queries.
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Amazon S3 Vectors Reaches GA, Introducing "Storage-First" Architecture for RAG
AWS has announced the general availability of Amazon S3 Vectors, increasing per-index capacity forty-fold to 2 billion vectors. By natively integrating vector search into the S3 storage engine, the service introduces a "Storage-First" architecture that decouples compute from storage, reducing total cost of ownership by up to 90% for large-scale RAG workloads.
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Uber Adopts Amazon OpenSearch for Semantic Search to Better Capture User Intent
To improve search and recommendation user experiences, Uber migrated from Apache Lucene to Amazon OpenSearch to support large-scale vector search and better capture search intent. This transition introduced several infrastructure challenges, which Uber engineers addressed with targeted solutions.
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Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads
Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services.
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Agentic Postgres: Postgres for Agentic Apps with Fast Forking and AI-Ready Features
Tiger Data, the company behind TimescaleDB, has launched Agentic Postgres, a Postgres-based database designed for both AI agents and developers. It extends Postgres with fast forking, an MCP server, native BM25 and vector search, and includes a CLI for terminal access.
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MySQL AI Introduced for Enterprise Edition
Oracle has recently announced MySQL AI, a new set of AI-powered capabilities available exclusively in the MySQL Enterprise edition, targeting analytics and AI workloads in large deployments. Concerns are rising throughout the MySQL community over the future of the popular Community edition, amid fears of vendor lock-in and following recent internal layoffs.
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LinkedIn Re-Architects Edge-Building System to Support Diverse Inference Workflows
LinkedIn has detailed its re-architected edge-building system, an evolution designed to support diverse inference workflows for delivering fresher and more personalized recommendations to members worldwide. The new architecture addresses growing demands for real-time scalability, cost efficiency, and flexibility across its global platform.
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AWS Introduces Vector Capabilities on Amazon S3
At the recent AWS Summit in New York City, AWS announced the preview of Amazon S3 Vectors, claiming to be the first cloud object store with native support for storing large vector datasets. The new option offers subsecond query performance, reducing the cost of storing AI-ready data compared to traditional vector databases.
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Yearly MariaDB LTS Release Integrates Vector Search
MariaDB has recently released MariaDB Community Server 11.8 as generally available, its yearly long-term support (LTS) release for 2025. The new release introduces integrated vector search capabilities for AI-driven and similarity search applications, enhanced JSON functionality, and temporal tables for data history and auditing.
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Redis 8 Targets AI Applications with New Data Type for Vector Similarity
Redis has recently announced the addition of Vector Set, a data type designed for vector similarity and a new option for AI applications. This new data type marks the first major contribution from Salvatore Sanfilippo (aka ‘antirez’), the creator of Redis, since rejoining the company.
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PlanetScale Vectors Now GA: MySQL's Missing Feature?
PlanetScale has recently announced that vector support is now generally available. Created as a fork of MySQL, this new feature allows storing vector data alongside an application's relational MySQL data, removing the need for a separate specialized vector database.