QuestDB is an open-source SQL database optimized for time-series data, capable of ingesting 4 million rows per second and executing queries in milliseconds. It addresses the challenges of high data cardinality and real-time analytics, providing a cost-effective solution that scales efficiently on both minimal and robust hardware.
Funding
$14.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
E1Founders
Product
Problem
Traditional databases often struggle with the unique demands of time-series data, leading to slow query performance and high infrastructure costs, especially when dealing with high data cardinality and real-time analytics requirements. Existing solutions may lack the necessary optimizations for efficient data ingestion, storage, and retrieval of time-stamped information.
Solution
QuestDB is an open-source SQL database engineered for time-series data, delivering high-performance ingestion and query capabilities. It is designed to handle massive volumes of time-series data with millisecond query execution, even under high cardinality. The database utilizes columnar storage, SIMD-optimized queries, and time-based data partitioning to achieve efficient data processing. QuestDB supports standard SQL with time-series extensions, enabling users to perform complex analytics with ease. It also integrates with popular tools like Grafana, Kafka, and Python, providing a versatile ecosystem for data analysis and visualization.
Target Audience
The primary target audience includes developers, data scientists, and engineers working with time-series data in industries such as finance, IoT, and real-time analytics, who require a high-performance, cost-effective database solution.
Features
- Columnar storage architecture optimized for time-series data
- SIMD-optimized queries for fast analytical processing
- Ingestion rate of up to 4 million rows per second per node
- Time-based data partitioning for efficient data retrieval
- Support for SQL and time-series specific SQL extensions
- Compatibility with open formats like Parquet and Arrow
- APIs for InfluxDB Line Protocol, REST, and Postgres
- Native Grafana plugin for data visualization
- Ability to query Parquet data directly from object storage