Millisecond Latency
Execute complex time-series queries across billions of rows in under 10ms. FluxQL's columnar engine is optimized from the ground up for temporal data.
Now in public beta
Query Time-Series Data at Any Scale
FluxQL is a blazing-fast query engine built for time-series workloads. Slice, aggregate, and transform billions of rows in milliseconds — no infrastructure headaches.
-- Aggregate CPU metrics in 5-minute windows
SELECT
time_bucket('5m', timestamp) AS bucket,
host,
avg(cpu_pct) AS avg_cpu,
p99(cpu_pct) AS p99_cpu
FROM metrics
WHERE timestamp BETWEEN
now() - INTERVAL '24h'
AND now()
AND region = 'us-east-1'
GROUP BY TIME '5m', host
ORDER BY bucket DESC
FILL 0;Trusted by engineering teams at
Acme Corp
DataStack
Voltron IO
NovaPulse
TimeWave
Everything you need to query at speed
Built for developers who don't want to fight their query engine.
Native Time Semantics
First-class support for time windows, downsampling, gap-filling, and interval aggregation — no plugins, no workarounds.
Any Scale, Any Source
Connect to Postgres, InfluxDB, Parquet files, or stream from Kafka. FluxQL speaks your data's language.
What developers are saying
"FluxQL cut our P99 query latency from 800ms to 6ms. It's the query layer we always wished existed."
"Finally a query engine that understands time as a first-class concept. Our dashboards are instant."
