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QuestDB

Challenger

London YC W20 fastest-growing open-source time-series database with 15K+ GitHub stars; $14.4M total ($12M Series A Nov 2021) with SIMD vector SQL serving investment banks and hedge funds competing with InfluxDB for high-frequency time-series.

69
AI Score
Grade B
AI Visibility Score (Beta)
Developer ToolsWebsiteUpdated March 2026

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.

Founded
2019
Curated content • Fact-checked and verified

Recent Activity

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blog_post
The mask that compiles to nothing: how HotSpot's JIT learned to reason about bits

A deep dive into the known-bits abstraction that recently landed in HotSpot's C2 JIT compiler: the same tristate-bit abstraction LLVM and GCC use, and why it lets the JVM delete redundant masks and shifts.

blog_post
Lies, Damn Lies and Database Benchmarks

We tweak one fair-but-different thing in each ClickBench scenario and watch the hot-run rankings reshuffle, a reminder to read benchmarks closely.

blog_post
QuestDB Enterprise 3.3.1: storage policies, custom CA, and finer-grained access control

QuestDB Enterprise 3.3.1 brings the new storage policy engine for tiering data to Parquet, posting indexes, a custom root CA for replication object stores, and column-level GRANT/REVOKE with EXCLUDE, on top of the QuestDB 9.4.2 engine.

blog_post
QuestDB 9.4.2: shareable queries, new aggregates, and a hardening pass

QuestDB 9.4.2 adds shareable Web Console queries, the array_agg and regr_r2 aggregates, and hardens Parquet and posting-index paths under heavy ingestion.

6-K
6-K — FORM 6-K

Foreign Filing filed 2026-06-05

blog_post
Aeron and QuestDB: building open infrastructure for capital markets data

How capital markets firms pair Aeron and QuestDB for exactly-once semantics, deterministic replay, and regulatory-grade history on open formats.

blog_post
One Trading runs a regulated 24/7 futures exchange on QuestDB

One Trading runs a regulated 24/7 futures exchange on QuestDB: 1.8M orders/sec, 5M+ rows/sec ingestion, real-time surveillance, room to scale.

6-K
6-K — FORM 6-K

Foreign Filing filed 2026-05-28

blog_post
QuestDB 9.4.0: Posting index, cross-column fill, and smarter Web Console

QuestDB 9.4.0 adds a posting index for SYMBOL columns with optional covering data, cross-column FILL(PREV) for SAMPLE BY, and Web Console autocompletion.

blog_post
How we made WINDOW JOIN parallel and vectorized

WINDOW JOIN aggregates one table over a time window around each row of another, made parallel and vectorized, then benchmarked vs Timescale, DuckDB, ClickHouse.

blog_post
Sparklines for traders: candlesticks and depth charts in SQL

QuestDB's bar(), sparkline(), ohlc_bar(), and depth_chart() functions render candlesticks and order book depth right inside SQL results, no notebook needed.

6-K
6-K — FORM 6-K

Foreign Filing filed 2026-04-24

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

69
↓ Declining

Based on estimated brand signals. Historical tracking coming soon.

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