Brand Intelligence Graph
Company Overview
About QuestDB
QuestDB is a London, United Kingdom-based open-source time-series database — backed by Y Combinator (W20) with $14.4-18 million in total funding including a $12 million Series A in November 2021 from Intel Ignite, Approx.vc, New Forge, and 468 Capital — providing financial services companies, IoT operators, and data infrastructure teams with the fastest time-series database globally (as measured by DB-Engines growth ranking), achieving 15,000+ GitHub stars through column-oriented storage, parallelized vector execution, SIMD CPU instructions, and low-latency SQL queries that enable blazingly fast ingestion and analysis of time-stamped data. Founded in 2019, QuestDB serves Tier 1/2 investment banks, leading hedge funds, national stock exchanges, and major crypto firms where microsecond-level query performance on time-series data is operationally critical.
Business Model & Competitive Advantage
QuestDB's high-performance time-series database addresses the throughput and latency limitations of general-purpose databases for time-stamped workloads: financial trading systems generating millions of tick data points per second, IoT sensor networks collecting readings from thousands of devices, and application metrics platforms ingesting thousands of events per second face a fundamental mismatch with row-oriented databases (PostgreSQL, MySQL) — inserting time-series data at high velocity in a row-oriented store creates write amplification, index contention, and query performance degradation that degrades trading system latency or IoT analytics responsiveness. QuestDB's columnar append-only architecture (optimized for high-rate time-series ingestion by appending new data without touching existing rows, with vector SIMD operations that process thousands of data points per CPU cycle during queries) achieves the ingestion throughput and query performance that financial and IoT time-series workloads require.
Competitive Landscape 2025–2026
In 2025, QuestDB competes in the time-series database, financial data infrastructure, and IoT analytics market with InfluxDB (dominant open-source time-series DB, $350M raised), TimescaleDB (PostgreSQL-based time-series, $55M raised), and ClickHouse (columnar OLAP database, $250M raised at $2B valuation) for financial firm, IoT operator, and data engineering team time-series database and high-frequency data infrastructure adoption. Intel Ignite's and 468 Capital's investments reflect both semiconductor-aligned performance computing conviction and European deep tech VC interest. Y Combinator W20 backing connects QuestDB with the database infrastructure investment community. The DB-Engines fastest-growing time-series database ranking validates developer and enterprise adoption velocity. The 2025 strategy focuses on the financial trading infrastructure market (market data ingestion, backtesting data stores, and real-time analytics), building the cloud-managed QuestDB Cloud offering, and expanding the Kafka and InfluxDB Line Protocol integration for hybrid data pipeline deployments.
Recent Activity
View all →QuestDB 9.4.0 introduces a compact posting index for SYMBOL columns with optional covering data, cross-column FILL(PREV) for SAMPLE BY, and a smarter Web Console with materialized view generation and context-aware autocompletion.
WINDOW JOIN is QuestDB's dedicated syntax for aggregating one table over a time window around each row of another. We parallelized it across page frames, used a low-cardinality join key to unlock a vectorized aggregation path, and benchmarked it against Timescale, DuckDB, and ClickHouse on a 50M x 150M row workload.
QuestDB now ships bar(), sparkline(), ohlc_bar(), and depth_chart() functions that render candlesticks and order book depth profiles directly inside SQL result sets, so you can see the shape of your data without leaving the terminal or the web console.
Foreign Filing filed 2026-04-24
Foreign Filing filed 2026-04-23
A community contribution ports HdrHistogram to off-heap memory for QuestDB's approx_percentile() function. The first benchmark is promising in parallel but regresses single-threaded. After a collaborative review, the regression is gone and the parallel speedup reaches 8.9x. Here is what changed.
Foreign Filing filed 2026-04-16
QuestDB 9.3.5 adds lateral joins, SQL-standard UNNEST for arrays and JSON, statistical window functions, multi-table HORIZON JOIN, and corrects SAMPLE BY timezone handling during DST transitions.
Three ways to load QuestDB time-series data into Python, then forecast cryptocurrency trading volume and volatility with Google's TimesFM foundation model - no training required.
QuestDB 9.3.4 brings dynamic RANGE bounds to WINDOW JOIN, Parquet row group pruning with bloom filters, new array analytics functions, and per-column Parquet encoding. QuestDB Enterprise 3.2.4 adds COPY PERMISSIONS and automatic permission cleanup.
How Arden Charts streams 15,000+ tickers across 8 exchanges, aggregates candlesticks in real time, and uses QuestDB materialized views to power a complete charting system on minimal hardware.
Benchmarks and an overview of ClickHouse versus QuestDB to compare features, functionality, performance, and ease of use.
Key Differentiators
Strong Challenger
QuestDB is an established challenger with significant market presence and competitive offerings in Developer Tools.
Frequently Asked Questions
Estimated Visibility Trend (Beta)
Simulated 8-week rolling score
Based on estimated brand signals. Historical tracking coming soon.
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