#vector-search

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New MariaDB release makes database management smarter and more secure

Vector search in MariaDB enhances AI initiatives by simplifying database management and facilitating effective searches of unstructured data.

Aerospike Vector Search adds self-healing live indexes

Aerospike's latest release improves real-time data ingestion and query performance with a self-healing HNSW index, supporting seamless integration for AI applications.

Amazon MemoryDB Provides Fastest Vector Search on AWS

Amazon MemoryDB now offers vector search with ultra-low latency, fastest performance, and highest recall rates among vector databases on AWS.

Why vector databases are having a moment as the AI hype cycle peaks | TechCrunch

Vector databases are essential for unstructured data and AI applications.

New MariaDB release makes database management smarter and more secure

Vector search in MariaDB enhances AI initiatives by simplifying database management and facilitating effective searches of unstructured data.

Aerospike Vector Search adds self-healing live indexes

Aerospike's latest release improves real-time data ingestion and query performance with a self-healing HNSW index, supporting seamless integration for AI applications.

Amazon MemoryDB Provides Fastest Vector Search on AWS

Amazon MemoryDB now offers vector search with ultra-low latency, fastest performance, and highest recall rates among vector databases on AWS.

Why vector databases are having a moment as the AI hype cycle peaks | TechCrunch

Vector databases are essential for unstructured data and AI applications.
moreai-applications
#semantic-search

Google Cloud Adds Scalable Vector Search to Memorystore for Valkey & Redis Cluster

Google Cloud's new scalable vector-search capabilities significantly enhance performance for applications relying on AI, providing ultra-low latency over vast datasets.

Implementing vector search with OpenAI, Next.js, and Supabase - LogRocket Blog

Vector search uses high-dimensional vectors to represent data for efficient similarity comparisons.
Semantic search focuses on understanding the meaning behind search queries for contextually relevant results.

Google Cloud Adds Scalable Vector Search to Memorystore for Valkey & Redis Cluster

Google Cloud's new scalable vector-search capabilities significantly enhance performance for applications relying on AI, providing ultra-low latency over vast datasets.

Implementing vector search with OpenAI, Next.js, and Supabase - LogRocket Blog

Vector search uses high-dimensional vectors to represent data for efficient similarity comparisons.
Semantic search focuses on understanding the meaning behind search queries for contextually relevant results.
moresemantic-search

Cockroach Labs CEO: Diverse database models are essential

Cockroach Labs CEO acknowledges MongoDB's advantages for developers, emphasizing the variety of approaches in the growing database market.

Cassandra 5.0 promises better search after indexing redesign

Cassandra 5.0 enhances performance and flexibility for AI applications with new features like Storage Attached Indexes and Vector Search.

MariaDB Introduces Open-Source Vector Preview, Aiming to Become Default MySQL Option

MariaDB 11.6 introduces public preview of vector search, aiming to outpace MySQL by offering open-source functionalities.

Pinecone launches its serverless vector database out of preview | TechCrunch

Pinecone launched Pinecone Serverless for easy deployment and scaling of AI products.
Customers demand dedicated tools for vector search, RAG, and language model applications with scale and cost-effectiveness in mind.
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