
Amazon Timestream
Serverless time-series database for IoT, metrics, and operational telemetry
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Blazing‑fast time‑series database for real‑time analytics with low‑latency SQL
QuestDB delivers sub‑millisecond ingestion and low‑latency SQL on columnar storage, supporting financial, IoT, and monitoring workloads via Docker, REST, PostgreSQL, and Grafana integrations.

QuestDB is designed for engineers and data teams that need to ingest high‑velocity time‑series data and run instant analytics. It shines in financial market data, IoT sensor streams, and real‑time monitoring dashboards where low latency and schema‑on‑the‑fly changes are essential.
The engine uses a column‑oriented, zero‑GC Java/C++ core with SIMD‑accelerated vector execution, delivering sub‑millisecond ingestion of millions of rows per second. SQL is extended with time‑series functions such as ASOF JOIN, SAMPLE BY, and LATEST ON, while materialized views and n‑dimensional arrays support complex analytics like order‑book depth. Multi‑tier storage moves data from a write‑ahead log to native columnar files and finally to Parquet on object storage, enabling hot‑warm‑cold data tiers without vendor lock‑in.
QuestDB runs from a single Docker container, Homebrew on macOS, or via Helm charts on Kubernetes, and is available as AMIs on AWS and images on GCP and DigitalOcean. Clients connect through PostgreSQL wire protocol, REST, or InfluxDB line protocol, and integrations with Grafana, Kafka, and popular data‑science libraries make it easy to build end‑to‑end pipelines.
When teams consider QuestDB, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Real‑time crypto trade analytics
Ingests millions of trade events per second and serves sub‑second queries for live price charts via Grafana.
Fleet sensor telemetry monitoring
Collects high‑cardinality IoT data streams, enabling instant anomaly detection dashboards.
Financial order‑book depth visualization
Stores 2‑D array order‑book data and provides fast ASOF JOIN queries for market depth analysis.
Historical taxi trip analysis
Archives billions of rows in Parquet for cost‑effective cold storage while supporting ad‑hoc SQL queries.
It automatically reorders rows during ingestion and deduplicates them, preserving exactly‑once semantics.
Yes, the engine can query native Parquet files stored in object storage without loading them first.
QuestDB offers PostgreSQL wire protocol, REST API, and InfluxDB line protocol for streaming ingestion.
The Web Console provides an interactive SQL editor, schema browser, and CSV import tools.
High‑availability and read‑replica features are available in the Enterprise edition.
Project at a glance
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