Sizing Your IIoT Table Before You Deploy

Industrial IoT PostgreSQL capacity planning should rely on measurements from a populated proof-of-concept table rather than nominal column widths, because tuple overhead, alignment, page pointers, and indexes can raise a 20-byte sensor record to roughly 95.6 bytes per row with one ingest-built index. The proposed method uses four inputs—tag count, sampling rate, measured bytes per row, and retention period—to project row counts, storage growth, cost, and required ingest throughput, supported by SQL size functions and pgbench testing against loaded tables. In the example, 10,000 tags reporting once per second for 24 months produce about 631 billion rows, require approximately 60.3 TB of storage, add 2.5 TB monthly, and need a sustained 10,000 inserts per second or 12,000 with headroom, while the tested two-core system reached only 8,719 inserts per second. Storage spending compounds as retained data accumulates, making longer retention substantially more expensive, while increases in tag count can quickly exceed both storage and ingest limits. The text recommends validating estimates in staging, testing growth scenarios before committing to a schema, and considering time-partitioned, compressed alternatives such as Tiger Data hypertables when conventional PostgreSQL projections fail budget or performance requirements.

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