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Head-to-head · Time-Series Databases

LindormTSDB vs Prometheus

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score LindormTSDB #3 in Time-Series Databases 9.0/10 Paid ✓ 3 of 3 features Visit Alibaba Cloud
Prometheus #5 in Time-Series Databases 8.8/10 Free plan Free plan✓ 1 of 3 features Visit Prometheus

LindormTSDB leads on 2 checks, Prometheus on 0, and 2 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreLindormTSDB · 9.0/10
  • Free planonly Prometheus
  • Most featuresLindormTSDB · 3 of 3

LindormTSDB scores higher on our rubric for time-series databases: 9.0 against 8.8 out of 10; our editors rank them #3 and #5.

On deployment, Prometheus gives you Self_hosted where LindormTSDB offers Cloud. LindormTSDB offers sql support; Prometheus doesn't. LindormTSDB offers horizontal scaling; Prometheus doesn't.

LindormTSDB is the better fit for managed compatible metrics and time-series workloads. Prometheus is the better fit for prometheus-native monitoring metrics.

  • LindormTSDB fits best

    Managed compatible metrics and time-series workloads

  • Prometheus fits best

    Prometheus-native monitoring metrics

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Side by side

Feature LindormTSDB 9.0/10 Visit ↗ Prometheus 8.8/10 Visit ↗
At a glance
Editor score 9.0 8.8
Ranking #3 in Time-Series Databases #5 in Time-Series Databases
Best for Managed compatible metrics and time-series workloads Prometheus-native monitoring metrics
Pricing model Paid Free
Starting price — Free plan
Free plan Not checked yet ✓ (best)
Free trial — —
Deployment Cloud Self-hosted
Platforms Web Web, Windows, macOS, Linux
Support Docs Community, Docs
Integrations 4 integrations 8 integrations
Built for Mid-market, Enterprise Small business, Mid-market, Enterprise
Features LindormTSDB 3/3 · Prometheus 1/3
SQL support ✓ (best) —
Retention policies ✓ ✓
Horizontal scaling ✓ (best) —
Specs
Deployment Cloud Self_hosted
Query languages SQL, PromQL, TSDB-compatible APIs and SDKs PromQL
Ingestion methods SQL INSERT via JDBC, InfluxDB line protocol, OpenTSDB API, Prometheus remote write HTTP pull scraping; Pushgateway; Remote Write; OpenMetrics backfilling
Our review
Pros
  • Supports SQL, PromQL, InfluxDB, OpenTSDB, and Prometheus workflows
  • Combines compression, downsampling, retention, and hot/cold tiering
  • Includes in-database forecasting and anomaly detection through Lindorm ML
  • PromQL supports selecting and aggregating labeled time-series data.
  • HTTP scraping, service discovery, and exporters support metric collection.
  • Recording rules, Alertmanager, federation, and remote storage extend monitoring.
Cons
  • Cloud deployment may not suit teams requiring self-managed infrastructure
  • Its broad interface set may add platform decisions for smaller workloads
  • Billing varies by region and configuration
  • No SQL support for querying time-series data.
  • Local storage is single-node rather than horizontally scaled.
  • Broader architectures require federation or remote-storage integrations.
Our verdict

LindormTSDB is Alibaba Cloud’s managed time-series database engine for measurement, device, IoT, telemetry, and monitoring data. It is designed for teams that need multiple ingestion and query paths rather than a single database interface.…

Read the review →

Prometheus is an open-source monitoring and alerting toolkit for infrastructure, applications, and services, particularly in dynamic and microservice-oriented environments. It collects numeric metrics through HTTP-based scraping and stores…

Read the review →
  1. LindormTSDBTime-Series Databases 9.0Paid
  2. PrometheusTime-Series Databases 8.8Free plan

Strengths and trade-offs

  • LindormTSDB — where it wins

    • Supports SQL, PromQL, InfluxDB, OpenTSDB, and Prometheus workflows
    • Combines compression, downsampling, retention, and hot/cold tiering
    • Includes in-database forecasting and anomaly detection through Lindorm ML

    Where it doesn't

    • Cloud deployment may not suit teams requiring self-managed infrastructure
    • Its broad interface set may add platform decisions for smaller workloads
    • Billing varies by region and configuration

  • Prometheus — where it wins

    • PromQL supports selecting and aggregating labeled time-series data.
    • HTTP scraping, service discovery, and exporters support metric collection.
    • Recording rules, Alertmanager, federation, and remote storage extend monitoring.

    Where it doesn't

    • No SQL support for querying time-series data.
    • Local storage is single-node rather than horizontally scaled.
    • Broader architectures require federation or remote-storage integrations.

More comparisons

All Time-Series databases comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update