As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...

Modern semantic search does not have to require a separate vector database. Data architects, database engineers, developers, or platform leaders can integrate Vertex AI and Cloud SQL vector indexes ...

A new SQL Server 2025 feature lets organizations run vector-based semantic searches on their own data, connecting to local or cloud-hosted AI models without relying on massive general-purpose LLMs. I ...

From AI-driven attacks to cutting-edge vector search capabilities, 2026 is redefining how we secure, optimize, and manage SQL databases. New SQL Server features, evolving threat landscapes, and modern ...

Vector database offers on-prem, cloud-native, or SaaS deployment, leading performance, a rich set of integrations and language drivers, and a dizzying array of optimization options. Efficient ...

Google is hosting a version of its Cloud Next conference in Tokyo this week, and it’s putting the focus squarely on tweaking its databases for AI workloads (because at this point in 2024, AI is the ...

SQL Server 2025 is introducing AI-native capabilities alongside new approaches for secure integration with large language models. Enterprises can now run local AI models such as Llama 3 via Ollama for ...

Overview RAG is transforming AI apps, and vector databases are the engine behind accurate, real-time responsesChoosing the ...

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...

Vector databases are all the rage, judging by the number of startups entering the space and the investors ponying up for a piece of the pie. The proliferation of large language models (LLMs) and the ...