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.
