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Head-to-head · IoT Analytics Software

Apache IoTDB vs Seeq

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score Apache IoTDB #1 in IoT Analytics Software 9.3/10 Open source ✓ 0 of 4 features Visit Apache IoTDB
Seeq #7 in IoT Analytics Software 8.6/10 Pricing on request ✓ 4 of 4 features Visit Seeq

Apache IoTDB leads on 0 checks, Seeq on 0, and 4 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 scoreApache IoTDB · 9.3/10
  • Most featuresSeeq · 4 of 4

Apache IoTDB scores higher on our rubric for iot analytics software: 9.3 against 8.6 out of 10; our editors rank them #1 and #7.

Apache IoTDB is the better fit for open-source IoT time-series analytics teams. Seeq is the better fit for industrial analysts needing advanced anomaly tools.

  • Apache IoTDB fits best

    Open-source IoT time-series analytics teams

  • Seeq fits best

    Industrial analysts needing advanced anomaly tools

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Side by side

Feature Apache IoTDB 9.3/10 Visit ↗ Seeq 8.6/10 Visit ↗
At a glance
Editor score 9.3 8.6
Ranking #1 in IoT Analytics Software #7 in IoT Analytics Software
Best for Open-source IoT time-series analytics teams Industrial analysts needing advanced anomaly tools
Pricing model Free Paid
Starting price Open source Pricing on request
Free plan Not checked yet Not checked yet
Free trial — —
Deployment Cloud, Self-hosted, Desktop Cloud, Self-hosted
Platforms Web, Windows, Linux Web
Support Community, Docs Email, Phone, Tickets, Community, Docs
Integrations 4 integrations 6 integrations
Built for Small business, Mid-market, Enterprise Mid-market, Enterprise
Features Apache IoTDB 0/4 · Seeq 4/4
Custom dashboards Not checked yet ✓ (best)
SQL querying Not checked yet ✓ (best)
Anomaly detection Not checked yet ✓ (best)
Machine learning tools Not checked yet ✓ (best)
Specs
Device limit Not checked yet Not checked yet
Data retention Not checked yet Not checked yet
Stream processing Not checked yet Near-real-time
Our review
Pros
  • SQL querying with tree and table data models
  • High-throughput ingestion with APIs, MQTT, REST, CSV, and TsFile
  • Retention controls, clustering, and broad analytics integrations
  • Multiple anomaly methods, including SOM, Isolation Forest, PCA, and clustering
  • Point-and-click analytics with dashboards and auto-updating reports
  • Supports SQL, Python notebooks, APIs, and custom ONNX prediction models
Cons
  • Requires self-managed deployment and operational ownership
  • Its IoT-native focus may exceed simpler analytics needs
  • Advanced use may require familiarity with IoTDB SQL dialects
  • Contact-sales pricing makes plan comparison less direct
  • Its industrial focus may exceed the needs of general-purpose analytics teams
  • Advanced workflows depend on connected historians, databases, or cloud data platforms
Our verdict

Apache IoTDB is an open-source, IoT-native time-series database for organizations managing large volumes of device and sensor data. It is designed for industrial applications including energy, transportation, aerospace, manufacturing, and…

Read the review →

Seeq is an industrial analytics platform for engineers, subject-matter experts, data scientists, and operations teams working with operational time-series data. It connects with industrial historians, SQL databases, cloud data platforms,…

Read the review →
  1. Apache IoTDBIoT Analytics Software 9.3Open source
  2. SeeqIoT Analytics Software 8.6Pricing on request

Strengths and trade-offs

  • Apache IoTDB — where it wins

    • SQL querying with tree and table data models
    • High-throughput ingestion with APIs, MQTT, REST, CSV, and TsFile
    • Retention controls, clustering, and broad analytics integrations

    Where it doesn't

    • Requires self-managed deployment and operational ownership
    • Its IoT-native focus may exceed simpler analytics needs
    • Advanced use may require familiarity with IoTDB SQL dialects

  • Seeq — where it wins

    • Multiple anomaly methods, including SOM, Isolation Forest, PCA, and clustering
    • Point-and-click analytics with dashboards and auto-updating reports
    • Supports SQL, Python notebooks, APIs, and custom ONNX prediction models

    Where it doesn't

    • Contact-sales pricing makes plan comparison less direct
    • Its industrial focus may exceed the needs of general-purpose analytics teams
    • Advanced workflows depend on connected historians, databases, or cloud data platforms

More comparisons

All IoT analytics software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update