TimescaleDB Enterprise for Data Centers
Postgres for scaling AI data center operations.
A high-performance Postgres foundation for facility telemetry, running securely in your own environment. Ingest 400k+ records per second, keep years of history on-prem, and query everything with SQL.
U41
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U37
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U33
Alert
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U29
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U25
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U21
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Inserts / sec
Compression
Retention
Postgres
01 // the problem
Modern data centers need more than legacy monitoring.
Every PDU, CRAC, chiller, server, switch, and sensor emits high-cardinality telemetry, hundreds of thousands to tens of millions of metrics per second. The conventional stack wasn't built for it, forcing you to compromise on history, SQL access, performance, or data ownership.
Where conventional tools break
Metric stores
Prometheus- and InfluxDB-class TSDBs buckle under per-sensor cardinality, lock you into a custom query language, and hold only weeks of history.
cardinality · short history
Cloud warehouses
Batch ELT adds minutes of latency and pulls raw telemetry off the floor.
too far from the metal
Historians
Proprietary historians lock telemetry behind closed formats with limited SQL. TimescaleDB Enterprise augments the historian as an open, queryable layer, so history stays in standard Postgres.
complements your historian
Open-source Postgres
Without native partitioning or compression, it bottlenecks on ingest under millions of high-cardinality rows per second.
ingest falls over
DCIM dashboards
Closed DCIM tools render charts but never expose the time-series: no SQL, no long-term history.
black box
02 // the architecture · near-edge to cloud
Local system of record. Cross-site data center visibility when you need it.
The near-edge cluster stays the source of truth. When data needs to leave the facility, Cloud Sync streams selected aggregates upstream to Tiger Cloud, one-way, push-only, and opt-in. Disable it and telemetry never leaves your perimeter.
PDUs · CRACs · BMCs · GPUs · switches
near-edge
Per-site system of record · same engine as cloud
Many sites · cross-site rollup · archive · shared dashboards
03 // capabilities
Built for sensor density, long retention, and SQL analytics.
Power, cooling, GPU, server, and network data streams in from every rack and hall. TimescaleDB Enterprise gives it a Postgres-native home.
INSERT INTO readings (ts, sensor_id, value)
SELECT ts, sensor_id, value
FROM staging_batch;
-- 10M rows/sec sustained, batched from collectorsHigh-ingest pipeline
Live
High-ingest pipeline
Ingest millions of time-ordered readings per second from PDUs, CRACs, chillers, GPUs, BMCs, switches, and sensors.
Compression
Keep years of raw telemetry online without letting storage costs explode.
Continuous aggregates
Maintain live PUE, WUE, capacity, and thermal dashboards without managing materialized-view sprawl.
Time-based partitioning
Automatically organize telemetry by time, site, hall, row, rack, and asset so queries hit the right data.
SQL joins
Join telemetry with asset inventory, maintenance events, tickets, and work orders directly in Postgres.
Postgres compatibility
Use the Postgres drivers, tools, and workflows your teams already know.
High availability
Run a resilient telemetry store with replicas, automated failover, backups, and point-in-time recovery.
Upgrade management
Managed Postgres and extension upgrades keep the store current with minimal downtime, replicas first.
Monitoring and observability
Built-in metrics and health insights for the database itself, so you operate the telemetry store with confidence.
04 // questions
Answers for facility engineers.
Architecture questions we hear from operators evaluating TimescaleDB Enterprise for their near-edge telemetry stack.
Now accepting early access requests
Postgres for every PDU, chiller, and GPU you run.
TimescaleDB Enterprise is in early access with a small group of data center operators. Design partners get direct access to Tiger Data engineering, roadmap influence, and white-glove onboarding. If you're running high-volume facility telemetry, let's talk.