Database Technology

AWS demonstrates using Kiro, an AI conversational assistant, alongside the awslabs.cloudwatch-mcp-server to query Amazon RDS logs. This setup shifts log analysis from manual, query-heavy tasks to a natural language interface that provides instant insights. The integration leverages the Model Context Protocol to connect the AI assistant directly to log data sources.

• Kiro enables natural language querying of RDS logs instead of traditional syntax-based searches.
• The awslabs.cloudwatch-mcp-server acts as the bridge between the AI and log data.
• This approach reduces the technical barrier for initial log review and troubleshooting.
• Practitioners can get immediate, actionable insights through conversational interaction.

AWS DMS CDC performance degrades when long-running transactions block redo log or transaction log consumption. The blog details how to monitor these bottlenecks across Oracle, PostgreSQL, MySQL, and SQL Server sources. It provides scripts to identify and resolve transactions that stall replication throughput.

• Long-running source transactions directly increase AWS DMS CDC latency by blocking log consumption.
• Monitoring strategies are provided for Oracle, PostgreSQL, MySQL, and SQL Server engines.
• Ready-to-use scripts help identify problematic transactions before they stall replication.
• Proactive resolution of blocking transactions is key to maintaining replication performance.

AWS has introduced performance optimizations from PostgreSQL 18 to Amazon Aurora and RDS, focusing on query efficiency and maintenance. Key features include skip scan optimization for multicolumn indexes, improved EXPLAIN output for debugging, and automatic removal of unnecessary self-joins. The update also brings several vacuum and autovacuum improvements to help maintain database health.

• Skip scan optimization boosts performance on multicolumn indexes.
• Enhanced EXPLAIN output aids in query plan analysis and tuning.
• Automatic removal of unnecessary self-joins simplifies query execution.
• Vacuum and autovacuum improvements help maintain table efficiency.
• Part 1 of a two-part series covering PostgreSQL 18 features.

The PostgreSQL community has released the first beta for version 19. This milestone marks the beginning of the feature freeze and testing phase leading up to the final stable release. It provides an opportunity for the community and enterprise users to validate new capabilities and performance improvements.

• PostgreSQL 19 enters the beta testing cycle with new features and optimizations.
• Users can download the beta to test compatibility and performance before final release.
• This release serves as the primary target for upcoming enterprise support cycles.

Percona has issued a security advisory for Percona Server for MongoDB addressing two high-severity memory-safety flaws, CVE-2026-11933 and CVE-2026-9740. These fixes will be bundled into a single coordinated release alongside ten other lower-scored CVE resolutions. The update targets both the upstream MongoDB Community edition and the Percona downstream distribution to mitigate these critical risks.

• Prioritize patching CVE-2026-11933 and CVE-2026-9740 due to their high severity and memory-safety nature.
• Expect a single coordinated release containing fixes for 12 total CVEs including the two critical ones.
• Verify that your Percona Server for MongoDB instances are updated to the latest patched version immediately.
• Monitor for follow-up advisories regarding the specific technical details of the memory-safety exploits.

Christophe Pettus analyzes the enable_mergejoin GUC, highlighting that merge joins perform optimally when input data is already sorted via an index. The post warns that forcing a merge join when data requires an explicit sort step can degrade performance due to the added sorting overhead.

• Merge joins are efficient only when data is pre-sorted by an index.
• Avoid forcing merge joins if the planner must pay for an explicit sort.
• Monitor enable_mergejoin settings to prevent unnecessary sort operations.
• Rely on the query planner's default choice unless specific bottlenecks exist.