QuestDB
Open-source time-series database with blazing SQL ingest and SIMD queries.
About
QuestDB is an open-source, column-oriented time-series database engineered for extreme ingestion throughput and low-latency SQL. The engine is zero-GC Java with C++ and Rust on the hot paths, memory-mapped time-partitioned columns, and SIMD vectorized query execution. It extends SQL with time-series operators like SAMPLE BY, LATEST ON, and ASOF/WINDOW/HORIZON joins, and speaks the PostgreSQL wire protocol plus the InfluxDB line protocol.
Started as a side project in 2014 by co-founder Vlad Ilyushchenko to solve time-series performance limits on trading desks, QuestDB was open-sourced under Apache 2.0 at the end of 2019. Storage is tiered from a parallel write-ahead log to native columnar partitions to Apache Parquet and Iceberg, so data stays open to Python, Spark, and DuckDB without export. It is the most direct open-source alternative for tick-data and high-frequency workloads that would otherwise need kdb+.
What it can do
- Millions of rows per second ingest with sub-millisecond SQL queries
- Time-series SQL extensions: SAMPLE BY, LATEST ON, ASOF and WINDOW joins
- PostgreSQL wire protocol plus InfluxDB line protocol ingestion
- Open storage formats: Parquet and Iceberg readable by any tool
Setup
docker run -p 9000:9000 -p 8812:8812 questdb/questdb, then use the web console on port 9000 or psql on port 8812.
Prerequisites
Time-ordered event data; Docker for the quickest start.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 98; Trending score 78/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.