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The title describes a set of index changes—eight dropped and three added—but provides no database engine, version, workload, measurement window, or production results. The counts are not independently verified here, and they do not show whether performance improved, worsened, or stayed the same.
That distinction matters: index-usage counters can help identify candidates for review, but their limits make a snapshot an unreliable stand-alone reason to remove an index. If you are considering similar changes, first establish what workload the evidence covers, then make changes reversible where possible and measure the outcome.
What the index counts do—and do not—tell us
Eight removals and three additions describe the claimed scope of the change, not its effect. Without a named database engine, before-and-after query measurements, or details of the workload, it is not possible to conclude that the changes reduced latency, improved throughput, saved storage, increased write performance, or preserved reliability.
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Index decisions involve trade-offs. An index may help some reads while adding maintenance work to inserts, updates, and deletes. Whether a particular change is beneficial depends on the queries and write activity the database actually handles. No such evidence is provided for this change.
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Why an index-use counter is not a deletion verdict
Usage statistics describe observed activity within a particular collection period. A low count may mean an index is rarely useful, but it may also reflect a short or unrepresentative observation window, statistics that have not yet caught up, or work that occurs infrequently. Check scheduled, batch, seasonal, and replica workloads as well as routine traffic before treating non-use as meaningful.
PostgreSQL 17
PostgreSQL 17 documents pg_stat_all_indexes as reporting a row for each index in the current database, with pg_stat_user_indexes covering user-table indexes. Statistics update periodically and may not include work still in progress. Interpret an index’s idx_scan alongside table statistics and query workload, and record the collection window rather than treating a low count as a general deletion rule. PostgreSQL 17 monitoring statistics documentation.
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SQL Server
Microsoft’s sys.dm_db_index_usage_stats reports user and internally generated usage information. Its user_updates counter reflects index maintenance associated with inserts, updates, or deletes. The counters start empty when the database engine starts, and the DMV does not return memory-optimized or spatial indexes. Record engine uptime and check index type before interpreting a usage snapshot as evidence of non-use. Microsoft’s index usage statistics documentation.
MySQL 8.4
MySQL 8.4 supports invisible indexes, which lets you test the effect of excluding an index from optimizer consideration without immediately dropping it. The manual describes visibility changes as fast, in-place operations; dropping and rebuilding an index can be expensive on a large table. This is a MySQL-specific option, not evidence that the change in the title involved MySQL. MySQL 8.4 invisible indexes documentation.
A safer way to evaluate index changes
- Identify the system and scope. Record the database engine and version, the affected indexes and tables, and whether any index supports a uniqueness rule or constraint. The engine is not identified for the changes described in the title.
- Define the observation window. Capture when usage data was collected and what it covers. Include infrequent and scheduled work, batch jobs, and relevant replicas; for SQL Server, note engine uptime because counters reset at startup.
- Use workload evidence, not just index counts. Review relevant queries and plans along with index and table statistics. A usage counter alone cannot establish the effect of an index on a particular query.
- Prefer a reversible test when the engine supports one. In MySQL 8.4, an index can be made invisible to test optimizer exclusion before a destructive drop. Do not assume the same mechanism exists or is appropriate in another engine.
- Measure after the change. Compare relevant query latency, read and write behavior, and any other production outcomes that matter to the workload. No before-and-after measurements are supplied for the eight removals or three additions.
- Keep a recovery path. Preserve the index definitions and understand the cost and process for restoring an index before removing it. Rebuilding may be expensive on a large table, as the MySQL 8.4 manual notes.
What remains unknown about these changes
- The database engine and version, and whether the claimed changes were made in production.
- The usage-statistics observation window and whether it covered scheduled, seasonal, batch, and replica workloads.
- Whether the removed indexes were unique, constraint-supporting, or used by infrequent queries.
- What evidence prompted the three additions.
- Whether query plans, latency, read/write behavior, or storage were measured before and after.
- Whether any production result was observed at all.
Until those details are available, the defensible account is limited: the title claims that eight indexes were dropped and three added, but no production statistic establishes the outcome. The changes may have been sensible, but the counts alone cannot demonstrate that they were safe or beneficial.
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