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Peak time-series performancePeaktime-seriesperformance

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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Ultra-low latency

SIMD-accelerated SQL queries
Multi-threaded engine
Ingest 5M rows/s

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Open architecture

Parquet + SQL — no lock-in
Postgres protocol compatible
Apache 2.0 open source

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Ready for scale

Petabyte-scale tiered storage
Multi-AZ resilience
Instant scale-out

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Standard SQL. No lock-in.

Developer friendly, easy-to-write SQL

-- Time-bucketing (SAMPLE BY)
SELECT
 timestamp, symbol,
 first(price) AS open,
 max(price) as high,
 min(price) as low,
 last(price) AS close,
 sum(amount) AS volume
FROM trades
WHERE timestamp IN today()
SAMPLE BY 1m FILL(PREV);

-- Streaming Materialized Views
CREATE MATERIALIZED VIEW 'bbo_1s'
 REFRESH IMMEDIATE AS (
 SELECT timestamp, symbol,
 last(bids[1][1]) AS bid,
 last(asks[1][1]) AS ask
 FROM market_data
 SAMPLE BY 1s
) PARTITION BY DAY TTL 1 DAY;

-- Multi-Dimensional Arrays
SELECT timestamp,
 array_sum(bids[2][1:4]) bid_vol,
 array_sum(asks[2][1:4]) ask_vol,
 bid_vol / ask_vol ratio
FROM market_data
WHERE
 timestamp > dateadd('h', -1, now())
AND symbol='EURUSD';

-- ASOF JOIN (Time-Bounded)
SELECT symbol,
 asks.price - bids.price as spread
FROM asks
ASOF JOIN bids
 ON symbol
 TOLERANCE 1s
WHERE
 asks.timestamp IN today();

Time-bucketing (SAMPLE BY)

Resample to fixed intervals; downsample; fill gaps with FILL (prev/linear/constant/none).

Streaming Materialized Views

Continuously compute OHLC bars and other rollups; REFRESH IMMEDIATE keeps dashboards live.

Multi-Dimensional Arrays

Compact 2D arrays for order-book snapshots; vectorized ops for depth/imbalance analytics.

As-of join (time-bounded)

Align each row to the latest event at or before its timestamp (ASOF JOIN … TOLERANCE).

LLMs speak SQL.
Your database should too.

Trained on billions of SQL statements, supercharge AI with our REST API in minutes.

QuestDB leaps forward

Scale fast.
Stay open.

Hot ingest for live analytics; Parquet archives for long-term insight. Open formats on object storage cut costs and end lock-in, while dataframe libraries and engines run natively on the data. AI-ready by design: standard SQL and REST API make prompt-to-query copilots work out of the box.

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.

Capital Markets

Powering Brazil's leading stock exchange

B3, the main stock exchange in Brazil and the largest in Latin America, leverages QuestDB for Capital Markets to power its Central Securities Depository (CSD) platform. The solution delivers high-performance, low-latency data management for real-time trading operations.

High performance: Engineered to capture terabytes of data per day with sub-millisecond query capabilities
Cloud-native architecture: Seamlessly integrates with microservices in cloud environments with 99.9% uptime guarantee
Open standards: Supports SQL queries and open formats like Parquet and Iceberg for historical data storage

"Our CSD platform demands exceptional performance, security, and resilience for real-time data. We chose QuestDB for its speed and straightforward deployment, which fits cleanly into our cloud-native architecture."

Kleber Almeida · B3

IT Manager

Read the press release

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

Open formats, no vendor lock-in

Delete proprietary, commit open

Run on open architecture that evolves without vendor lock-in. Native Parquet, Arrow, Iceberg and SQL plug straight into modern AI/ML.

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

Peak performance time-series

Hyper ingestion

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 Engine

High Availability

N-Dimensional Arrays

Data Deduplication

Using QuestDB, we deliver real-time market data from a top 10 blockchain. This outperforms a legacy cloud-based data platform at a fraction of the cost, reducing TCO by more than 90%.

Daniel Siedentopf — Senior Developer, XRP Ledger Foundation

QuestDB performance compared to TimescaleDB and InfluxDB. QuestDB is the clear winner.

Use QuestDB with the tools you love

Simple connections with clients, brokers, data-feeds, and much more.

Upgrade from legacy systems

QuestDB for Capital Markets

Built for tick data, trades, order books, and OHLC-with nanosecond timestamps, ASOF joins, arrays, and materialized views. Query years of history in milliseconds with standard SQL.

Learn more about QuestDB for Capital Markets

QuestDB is an essential part of our trading platform—giving us a high-speed, scalable store for billions of trades that we can query in real time to power both customer-facing features and internal systems.