Timescale is an Analytical Databases company founded in 2015 and based in New York, United States. It has raised $165.6M in total funding, most recently a Series C in 2022 at a $1B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Feb 1, 2022 | Series C | $109.5M | $1B | — |
| May 5, 2021 | Series B | $40M | — |
| Redpoint Ventures |
| Jan 1, 2018 | Series A | $12.4M | — | — |
| Jan 1, 2016 | Seed | $3.7M | — | — |
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A PostgreSQL extension that adds hypertables, continuous aggregates, and columnar compression for high-performance time-series workloads while preserving full SQL compatibility and the complete Postgres ecosystem. Used for IoT sensor data, infrastructure monitoring, financial tick data, and application event time series. TimescaleDB 2.26 delivers 3.5x faster time_bucket() aggregations and 70x faster summary queries versus prior versions.
A fully managed TimescaleDB-as-a-service with automatic scaling, native data tiering to Amazon S3 for cost-efficient long-term retention, and built-in query optimization. Targets DevOps, IoT, and analytics teams that need time-series performance without tuning Postgres internals. Includes retention policies, compression automation, and continuous aggregate refresh to keep analytical dashboards current without manual pipeline maintenance.
A Python library and PostgreSQL extension that transforms Postgres into a RAG and semantic search backend by automating vector embedding generation and synchronization from database tables and S3 documents. Supports embedding inference from OpenAI, Anthropic, Cohere, and local Ollama models called directly from SQL. The pgai Vectorizer is compatible with any Postgres deployment including self-hosted, Amazon RDS, and Supabase, enabling AI features without a separate vector database.