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title: Comparing MongoDB, TimescaleDB, InfluxDB, and CrateDB...
description: A comparison of four databases commonly evaluated for industrial IoT workloads: MongoDB, TimescaleDB, InfluxDB 3, and CrateDB. The analysis covers ingest...
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# Comparing MongoDB, TimescaleDB, InfluxDB, and CrateDB for an IIoT Use-case

**[CrateDB](https://daily.dev/sources/cratedb)** · 10 min read · 0 upvotes · 0 comments

## Summary

A comparison of four databases commonly evaluated for industrial IoT workloads: MongoDB, TimescaleDB, InfluxDB 3, and CrateDB. The analysis covers ingest throughput, query performance over long time ranges, SQL join capability, schema flexibility, and deployment options including on-premises. MongoDB struggles with index memory at scale and lacks native time-series SQL. TimescaleDB works well for moderate PostgreSQL-based deployments but removed self-hosted horizontal scaling in v2.14. InfluxDB 3 improved high-cardinality handling via Parquet/Arrow storage but lacks cross-system joins and has a migration burden for v2.x users. CrateDB is positioned as the strongest fit for high-cardinality sensor data requiring SQL joins across sensor, asset, and production data, with native distributed scaling and on-premises support. A side-by-side table and decision guide help teams choose based on their specific workload profile.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cratedb.com/blog/comparing-databases-industrial-iot-use-case>

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---

Tags: [#iot](https://daily.dev/tags/iot), [#influxdb](https://daily.dev/tags/influxdb), [#timescaledb](https://daily.dev/tags/timescaledb), [#cratedb](https://daily.dev/tags/cratedb)

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