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Database Technology

Saturday, August 29, 2026 · 6 stories, curated & summarized — click any story for the source.

AWS has released Aurora MySQL 3.13, aligning with MySQL 8.0.45 to include community fixes and Aurora-specific enhancements. Users can upgrade via automatic minor version updates during maintenance windows or through in-place and snapshot restore methods. The update is available in all regions supporting Aurora MySQL.

  • Aurora MySQL 3.13 brings MySQL 8.0.45 compatibility and specific engine improvements
  • Enable automatic minor version upgrades to streamline patching across clusters
  • Use AWS Organizations Upgrade Rollout Policy for phased, controlled deployments
  • Supports both in-place upgrades and snapshot restore for minor version changes
CHECKLISTAurora MySQL 3.13 Upgrade GuideEnable automatic minor version upgrades for streamlined patchingUse AWS Organizations Upgrade Rollout Policy for phased deploymentsChoose in-place upgrades or snapshot restore methodsVerify cluster compatibility with MySQL 8.0.45 features

Pavel Stehule has completed a patch allowing Lua scripts to run within the psql interactive terminal. The implementation enables complex client-side logic, demonstrated by a custom VACUUM wrapper that enhances verbose output readability. A key feature is real-time progress reporting, achieved by polling pg_stat_progress_vacuum every second during long-running maintenance operations.

  • psql now supports Lua scripting for advanced client-side automation and UI customization.
  • Developers can create custom commands with real-time progress bars for long-running tasks.
  • The patch is available via the okbob/lua-psql GitHub repository for testing and integration.
HOW IT WORKSLua in psql Workflow1Write Lua script2Run via psql3Execute client logic4Poll progress stats5Display real-time output

A pg_dump data-only restore fails when unqualified table names in triggers cannot be resolved, even if the tables exist in the schema. This occurs because pg_dump explicitly sets search_path to an empty string at the start of the dump to ensure deterministic behavior. Consequently, any SQL statements referencing tables without a schema prefix, such as those inside AFTER INSERT triggers, throw relation does not exist errors during restoration.

  • pg_dump forces search_path to empty string, requiring fully qualified table names.
  • Triggers referencing tables by bare name will fail during data-only restores.
  • Schema-qualify all table references in triggers to ensure dump compatibility.
  • Data-only restores are not immune to schema resolution issues caused by search_path.
CHECKLISTFix Pg_dump Trigger ErrorsSchema-qualify all table references in triggersAvoid bare table names in SQLVerify triggers before data-only restoresCheck search_path settings in dumps
Planet PostgreSQL database

PostgreSQL Log Rotation: Aligning Age, Size, and Truncation

Christophe Pettus details the interplay between log_rotation_age, log_rotation_size, and log_truncate_on_rotation in PostgreSQL. These three GUCs work together to manage how and when log files are rotated and cleaned up. Understanding their combined behavior is essential for maintaining predictable logging environments without data loss.

  • Rotation triggers based on time intervals or file size limits independently.
  • Truncation setting determines if old logs are overwritten or preserved.
  • Parameters must be configured together to avoid unexpected log behavior.
  • Review current GUCs to ensure rotation aligns with compliance needs.
  • Test changes in staging to verify log file lifecycle expectations.

Hubert Lubaczewski evaluates two external modules, pg_tre and pg_re2, which bring alternative regular expression engines to PostgreSQL. Using execution plans from explain.depesz.com as test data, he benchmarks these extensions against standard regex capabilities. The analysis highlights potential performance gains and functional differences for complex pattern matching workloads.

  • pg_tre and pg_re2 offer alternative regex backends for PostgreSQL beyond the default engine
  • Performance varies significantly based on query complexity and data volume
  • Benchmarking against real-world execution plans reveals specific optimization opportunities
  • These extensions may improve throughput for heavy text processing tasks
HOW IT WORKSRegex Benchmarking Pipeline1Select real-world execution plans2Integrate pg_tre and pg_re2 modules3Benchmark against standard regex engine4Analyze performance gains and differences
AWS What's New awsdatabase ↺ since 08-28

Aurora DSQL adds foreign key constraints for referential integrity

Amazon Aurora DSQL now supports foreign key constraints on new and existing tables, allowing developers to enforce relational rules directly in the database. The system rejects writes that would leave a record pointing to a non-existent parent row, ensuring data consistency across the distributed, multi-Region cluster. Administrators can configure deletion and update behaviors using standard options like CASCADE, RESTRICT, and SET NULL.

  • Enforce referential integrity natively in Aurora DSQL without application-level checks.
  • Supports NO ACTION, RESTRICT, CASCADE, SET NULL, and SET DEFAULT actions.
  • Applies to both new and existing tables in compatible AWS Regions.
  • Maintains PostgreSQL compatibility while adding strict relational constraints.
CHECKLISTAurora DSQL Foreign Key ActionsEnforce referential integrity nativelySupport CASCADE and RESTRICT actionsApplies to new and existing tablesMaintains PostgreSQL compatibility
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