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The high-performance
time series database,
built for AI agentsThe high-performance time series database, built for AI agents

QuestDB is the open-source time-series database for demanding workloads—from trading floors to mission control. It delivers ultra-low latency, high ingestion throughput, and a multi-tier storage engine. Native support for Parquet and SQL keeps your data portable, AI-ready—no vendor lock-in.

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Powering critical data workloads at leading companies globally

“QuestDB brings a SQL-first solution able to ingest data at speed.”

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99.9%

Uptime with QuestDB Enterprise

“QuestDB is used at Airbus for real-time applications involving billions of data points per day.”

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8 million

Rows per second ingestion throughput

Details

“QuestDB has become the standard for data aggregation.”

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5,000+

Queries/second from a single instance

Case study

“QuestDB is a time series database truly built by developers for developers”

Details

$170B

Annual transactions across 1,000+ assets

QuestDB wins Best Trading Analytics Platform at the TradingTech Insight Awards Europe 2026.

TradingTech Insight Awards Europe 2026 Winner — QuestDB — Best Trading Analytics Platform

Why QuestDB

AI is rewriting data infrastructure.
We’re at its core.

Legacy data infrastructure is being rewritten because of AI, cost pressures,
and vendor lock-in. QuestDB is built for it.

Performance at scale

10x faster ingest than the next-fastest database
Purpose-built for latency-sensitive workloads
In production at tier-1 firms in capital markets, aerospace, and energy

Compare to incumbents

Open and AI-ready

One SQL surface across real-time and historical tiers
AI agents query QuestDB with the SQL they already know
Open data lake on Parquet, Iceberg; unified and portable

Explore the multi-tiered architecture

Built for production

Operated by your team, no specialist consultants required
Scales horizontally with distributed architecture
High availability with multi-AZ resilience

Explore QuestDB Enterprise

16M+Rows/sec ingest

120M+Rows/sec egress

60%Lower TCO

<10msQuery latency

16M+Rows/sec ingest

120M+Rows/sec egress

60%Lower TCO

<10msQuery latency

Ingest & egress performance on

QuestDB v10.0

Standard SQL. no lock in.

Easy to write SQL for developers and agents

Special SQL primitives for time-series, built for the most demanding workloads on the trading floor, expanding into aerospace and beyond. Easy for engineers to write, native for AI agents.

coding agent - ~/questdb-demo

Prompt:

"Create a matview to compute 1-minute OHLCV candles from market_data"

All prompts

Trusted by exchanges and banks in production

QuestDB Customers

Capital Markets B3 logo

B3 powers Latin America's largest exchange with QuestDB

B3's Central Securities Depository platform runs on QuestDB for Capital Markets, processing every trade on the world's tenth-largest exchange.

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“We chose QuestDB for its speed and straightforward deployment, which fits cleanly into our cloud-native architecture.”

Kleber AlmeidaIT Manager, B3

$5B+Daily traded volume

99.9%Uptime guarantee

Capital Markets

One Trading runs regulated digital asset trading on QuestDB

One Trading's regulated crypto exchange runs on QuestDB for Capital Markets, ingesting billions of trades for real-time market surveillance and latency analysis.

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“QuestDB is an essential part of our trading platform — a high-speed, scalable store for billions of trades we can query in real time.”

Steven HarperChief Security Officer, One Trading

8M+Rows/sec ingest

1stEuropean MiFID II derivatives exchange

Capital Markets

BTG Pactual replays order books and tunes pricing algos on QuestDB

BTG Pactual replays order books and analyzes pricing algorithm performance on QuestDB for Capital Markets, and runs the same platform under their real-time equities market data API.

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“QuestDB has become the standard for data aggregation — lightning fast, serving raw live intraday data through our APIs in a few milliseconds.”

Renan AvilaDirector, BTG Pactual

<10msAPI response time

100K+Tickers per table

Experience QuestDB now

Explore our live demo

Our live demo instance is the quickest way to get a feel for QuestDB. Scan more than 2 billion rows in milliseconds. Example queries can get you deep in just a few clicks.

/* This query takes the best bid price and multiplies it by 1.01. Then it finds the level at which that price would be met inside the prices array. We slide the volume array from the first level until the level we found, and sum all the volumes. Note the use of DECLARE to make the query more readable. */

DECLARE
  @prices := asks[1],
  @volumes := asks[2],
  @best_price := @prices[1],
  @multiplier := 1.01,
  @target_price := @multiplier *  @best_price,
  @rel_vol := @volumes[
    1:insertion_point(@prices, @target_price)
  ]
SELECT timestamp, array_sum(@rel_vol) total_volume
FROM market_data
WHERE timestamp > dateadd('m', -1, now())
AND symbol='EURUSD';

Launch demo and see result

AI models and coding agents connecting to QuestDB

LLMs speak SQL.
Your database should too.

Models speak SQL and read open formats like Parquet and Iceberg. QuestDB supports both, exposed via a REST API,
so one prompt moves an agent from intent to executed query, with no proprietary client in between.

QuestDB for AI Agents

From real-time ingest to open data lake

Delete proprietary, commit open

Ingested data is offloaded into an open data lake in Parquet format, with automatic tiering. One SQL surface queries real-time and historical data across all tiers. If you're already using Python, point your dataframe libraries and AI frameworks at the Parquet files directly, no export needed.

timestamp

symbol

price

volume

2025-01-01T00:00:00.000

EURUSD

1.0847

2500000

2025-01-01T00:00:01.000

GBPUSD

1.2734

1800000

2025-01-01T00:00:02.000

USDJPY

149.82

3200000

2025-01-01T00:00:03.000

AUDUSD

0.6452

1200000

2025-01-01T00:00:04.000

USDCAD

1.3765

1500000

2025-01-01T00:00:05.000

USDCHF

0.8834

900000

Azure Blob

Amazon S3

NFS

One SQL engine, multiple storage tiers

Real-time and historical data, in one engine.

WHERE symbol in ('AAPL', 'NVDA')

LATEST ON timestamp PARTITION BY symbol

CREATE MATERIALIZED VIEW 'trades_OHLC'

min(price) AS low

timestamp IN today()

SELECT spread_bps(bids[1][1], asks[1][1])

FROM read_parquet('trades.parquet')

SAMPLE BY 15m

Tier One: Hot ingest (WAL), durable by default

Incoming data is appended to the write-ahead log (WAL) with ultra-low latency. Writes are made durable before any processing, preserving order and surviving failures without data loss. The WAL is asynchronously shipped to object storage, so new replicas can bootstrap quickly and read the same history.

Tier Two: Real-time SQL on live data

Data is time-ordered and de-duplicated into QuestDB's native, time-partitioned columnar format and becomes immediately queryable. Power real-time analysis with vectorized, multi-core execution, streaming materialized views, and time-series SQL (e.g., ASOF JOIN, SAMPLE BY). The query planner spans tiers seamlessly.

Tier Three: Cold storage, open and queryable

Older data is automatically tiered to object storage in Apache Parquet. Query it in-place through QuestDB or use any tool that reads Parquet. This delivers predictable costs, interoperability with AI/ML tooling, and zero lock-in.

Open by Design

Open source. Open standards.

AWS

GCP

Open at every layer

Download

License: Apache 2.0
Open standards: Parquet, SQL, PGWire
Community: 200+ OSS contributors

Need more?

CompareCompare Enterprise & OSS

Reliability: HA, replication, failover
Scale: Multi-tier storage at petabyte scale
Security: RBAC, TLS, SSO
Support: 24/7 expert support, 99.9% uptime SLA

Get a demo

Open at every layer

Download

License: Apache 2.0
Open standards: Parquet, SQL, PGWire
Community: 200+ OSS contributors

Need more?

CompareCompare Enterprise & OSS

Reliability: HA, replication, failover
Scale: Multi-tier storage at petabyte scale
Security: RBAC, TLS, SSO
Support: 24/7 expert support, 99.9% uptime SLA

Get a demo

Peak performance time-series

Time-series
ingestion at scale

Write-ahead logging (WAL) for instant durability; time-partitioned columnar engine for speed. Ingest millions of rows/sec and query with SIMD-optimized SQL.

Storage EngineView

High AvailabilityView

N-Dimensional ArraysView

Data DeduplicationView

Denys RtveliashviliHead of Data, Laser Digital (Nomura Group)

Faster ingestion than leading competitors in open source benchmarks (TSBS)

Plug QuestDB into the tools
your team already uses.

Native integrations across the modern open data stack.

Postgres Grafana Kafka Pandas Redpanda Python

Real-time analytics for high performance workloads

Built for the most demanding
time-series use cases

View all use cases

Capital Markets

Pre- and post-trade, in real time

Millisecond SQL on the trading floor, plus an open Parquet data lake for quants to backtest on full history.

Explore QuestDB for Capital Markets

Crypto

High-speed, multi-exchange crypto market data

Continuously ingest tick and order-book streams from dozens of exchanges, run native SQL analytics, and keep on-chain balances exact.

View real-time OKX crypto dashboard

Aerospace

Real-time insights from in-flight to ground control

Ingest millions of sensor readings per second from aircrafts, rockets, satellites, and jet-engine simulations.

Energy Infrastructure

Smarter grids, faster decisions

Energy firms supplying AI datacenters use QuestDB to ingest SCADA, MQTT, and grid telemetry in real time, with years of history on cost-efficient object storage.

Robotics

Physical AI & robotics telemetry

From sensor streams to control logs, QuestDB captures every signal from robot fleets in real time, with full history on object storage for replay, training, and fleet observability.

Retail Banking & Payments

Fraud analytics engine: low-latency ingest, high-concurrency reads

Millisecond SQL scoring across high-cardinality accounts, devices, and merchants—backed by multi-tier storage and open formats for ML.

4.8/5 G2 Rating

Ready for production?

QuestDB Enterprise adds high availability, security, multi-AZ resilience, a fully distributed architecture for scale, and 24/7 support. For teams running mission-critical workloads.

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