Top 26 Vector Database Software SaaS Companies in May 2026

Palo Alto, California, United States

Provider of an open source in-memory data grid platform designed to modernize existing applications. The company's open source in-memory data grid platform with installed clusters offer operational in-memory computing, enabling companies to manage their data and distribute processing using in-memory storage and parallel execution for breakthrough application speed and scale.

Berlin, Germany

Qdrant is an open-source vector search engine. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.

Trondheim, Trøndelag, Norway

Redwood City, California, United States

Database for Real-time Analytics and Hybrid Search.

Reno, Nevada, United States

Positron delivers vendor freedom and faster inference for both enterprises and research teams, by allowing them to use hardware and software explicitly designed from the ground up for generative and large language models (LLMs). Through lower power usage and drastically lower total cost of ownership (TCO), Positron enables you to run popular open source LLMs to serve multiple users at high token rates and long context lengths. Positron is also designing its own ASIC to expand from inference and fine tuning to also support training and other parallel compute workloads.

New York, New York, United States

Timescale is addressing one of the largest challenges (and opportunities) in databases for years to come: helping developers, businesses, and society make sense of the data that humans and their machines are generating in copious amounts. TimescaleDB is the only open-source time-series database that natively supports full-SQL, combining the power, reliability, and ease-of-use of a relational database with the scalability typically seen in NoSQL systems. It is built on PostgreSQL and optimized for fast ingest and complex queries. TimescaleDB is deployed for powering mission-critical applications, including industrial data analysis, complex monitoring systems, operational data warehousing, financial risk management, and geospatial asset tracking across industries as varied as manufacturing, space, utilities, oil & gas, logistics, mining, ad tech, finance, telecom, and more. Timescale is backed by NEA, Benchmark, Icon Ventures, Redpoint Ventures, Two Sigma Ventures, and Tiger Global. Documentation: https://docs.timescale.com GitHub: https://github.com/timescale/timescaledb Twitter: https://twitter.com/timescaledb