Logo
Deploy Now

SaaS Alternative

Datadog

Categories

Monitoring Analytics Database IoT Big Data Time Series Financial Data

Stars

17,268

Forks

1,639

Watchers

134

Developer links

Last Updated: 08-21-2026 04:34 PM (UTC)

QuestDB

Powering trading floors at firms processing millions of market data events per second and trusted by organizations including Airbus, Yahoo, and Copenhagen Atomics, QuestDB has earned over 17,000 GitHub stars as the time-series database that refuses to make you choose between ingestion speed and query latency. The column-oriented, time-partitioned storage engine processes millions of rows per second on ingest through write-ahead logging with instant durability, while SIMD-accelerated parallel execution returns analytical queries over billions of rows in milliseconds. Time-series SQL extensions add ASOF JOIN for point-in-time lookups across tables with misaligned timestamps, SAMPLE BY for downsampling at arbitrary time intervals, LATEST ON for last-value queries, and WINDOW JOIN for sliding window aggregations — all through standard SQL syntax accessible via the PostgreSQL wire protocol, REST API, or the QuestDB Wire Protocol (QWP) that streams Apache Arrow at 220 million rows per second. Multi-tier storage automatically moves data from the WAL through native columnar format to Parquet files on S3-compatible object storage, keeping hot data fast and cold data portable without manual tiering. The built-in web console provides an interactive SQL editor with syntax highlighting, autocomplete, and charting for quick data exploration. Views, materialized views, and n-dimensional arrays support real-time analytics, while native Parquet export enables direct integration with Python, DuckDB, and AI/ML frameworks. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

QuestDB
QuestDB
QuestDB
QuestDB
QuestDB

Benefits

  • Millions of Rows Per Second
  • Ingest millions of time-series events per second through write-ahead logging with instant durability, handling trading floors, IoT sensors, and infrastructure metrics at scale.
  • SIMD-Accelerated SQL Queries
  • Execute analytical queries over billions of rows in milliseconds using SIMD instructions, parallel vectorized execution, and time-partitioned columnar storage optimization.
  • Time-Series SQL Extensions
  • Query with ASOF JOIN for point-in-time lookups, SAMPLE BY for downsampling, LATEST ON for last-value retrieval, and WINDOW JOIN for sliding aggregations using standard SQL.
  • Multi-Tier Parquet Storage
  • Automatically tier data from WAL through native columnar format to Parquet on S3-compatible object storage, keeping hot data fast and cold data portable without manual intervention.

Features

  • Web SQL Console
  • Explore data through a built-in web console with interactive SQL editor, syntax highlighting, autocomplete, and integrated charting for instant visualization.
  • PostgreSQL Wire Protocol
  • Connect using any PostgreSQL client, driver, or ORM through PGwire compatibility, plus REST API and QuestDB Wire Protocol for high-throughput binary streaming.
  • Materialized Views
  • Create continuously updated materialized views that pre-aggregate time-series data for dashboard queries, reducing latency for frequently accessed metrics.
  • Native Parquet Integration
  • Export and read Parquet files natively for direct integration with Python DataFrames, DuckDB, Apache Spark, and AI/ML frameworks without intermediate conversion.
  • Grafana Integration
  • Visualize time-series data in Grafana dashboards using the official QuestDB data source plugin with optimized query translation and variable support.