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Database Technology

Wednesday, July 08, 2026 · 7 stories, curated & summarized — click any story for the source.

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AWS What's New awsdatabase

AWS RDS for Oracle adds support for Database 26ai with Bedrock and Vector Search

Amazon RDS for Oracle now supports Oracle Database 26ai, the latest Long Term Support release, integrating directly with Amazon Bedrock for foundation model access. This update enables developers to use Oracle Select AI for natural language SQL generation and implement Retrieval Augmented Generation (RAG) natively. The release introduces AI Vector Search, allowing vector embeddings and semantic similarity searches to coexist with relational data and JSON without external vector databases.

  • Oracle Database 26ai is now available on RDS as a Long Term Support release.
  • Native Amazon Bedrock integration provides access to Claude, Nova, and Llama models.
  • Select AI allows SQL query generation and execution via natural language prompts.
  • RAG can be implemented directly in SQL using Oracle AI Vector Search.
  • Vector embeddings and hybrid searches are supported alongside relational data.

Fleet impact: Plan migration paths for RDS Oracle instances to 26ai to leverage native vector search and reduce reliance on external vector stores. Evaluate Select AI capabilities for developer productivity and verify Bedrock integration requirements for your specific RAG workloads.

HOW IT WORKSBuilding RAG with Oracle 26ai1Connect Oracle RDS to Amazon Bedrock2Ingest data into Oracle Vector Search3Generate embeddings using foundation models4Run semantic queries via Select AI
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Percona Blog database

Percona Operator for MySQL 1.2.0 adds cross-site replication and encrypted backups

Percona Operator for MySQL version 1.2.0 introduces capabilities for multi-region deployments, including cross-site replication to establish warm replicas in separate data centers. The release also supports encrypted backups stored in object storage to meet compliance requirements. Additionally, the operator now features automatic storage scaling to handle growing data volumes without manual intervention.

  • Enables warm replica clusters in secondary regions for improved disaster recovery.
  • Supports encrypted backups in object storage for audit compliance.
  • Automates storage scaling to reduce operational overhead for growing datasets.
  • Addresses common scaling gaps for fleets moving beyond single-cluster deployments.
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AWS Database Blog awsdatabase

RDS PostgreSQL 18 boosts logical replication with generated columns and auto-cleanup

Amazon RDS for PostgreSQL 18 introduces significant enhancements to logical replication, including support for replicating STORED generated columns via a new parameter. The update enables default parallel streaming and allows toggling two-phase commit on active subscriptions. Operational visibility improves with new counters in pg_stat_subscription_stats for monitoring conflicts.

  • Replicate STORED generated columns using the publish_generated_columns parameter.
  • Parallel streaming is now enabled by default for better throughput.
  • Monitor replication conflicts using new counters in pg_stat_subscription_stats.
  • Configure idle_replication_slot_timeout for automatic slot cleanup.
  • Toggle two-phase commit on a running subscription without restart.

Fleet impact: For RDS PostgreSQL and Aurora fleets, this simplifies schema synchronization for generated columns and reduces manual maintenance via auto-cleanup. Check pg_stat_subscription_stats to audit conflict rates and verify parallel streaming is active to ensure optimal replication performance.

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PostgreSQL News database

PDU: Open Source PostgreSQL Data Unloader for Offline Recovery

PostgreSQL Data Unloader (PDU) is a new open-source tool designed to recover data from offline instances where normal SQL tools are unavailable. It directly reads data files and WAL archives to reconstruct metadata and export tables or schemas as CSV without modifying the original directory. The tool also supports targeted row recovery from WAL logs to handle accidental DELETE or UPDATE operations.

  • PDU enables full-database or targeted table exports via CSV when PostgreSQL is down.
  • It reads raw data files and WAL archives without altering the original data directory.
  • Supports targeted row recovery from WAL for accidental DELETE/UPDATE incidents.
  • Reconstructs database, schema, and table metadata automatically during offline analysis.
HOW IT WORKSRecovering Data with PDU1Read raw data files2Analyze WAL archives3Reconstruct metadata4Export CSV files
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Hacker News (100+ points) general

PgDog authors explain why they built yet another Postgres connection pooler

The PgDog team details the architectural decisions behind their new Postgres connection pooler, addressing limitations in existing tools like PgBouncer. They highlight specific use cases where their solution offers improved performance or feature parity for high-throughput environments. The post outlines the trade-offs made during development to ensure better resource utilization and connection management.

  • Existing poolers may lack specific performance optimizations for high-concurrency workloads
  • PgDog offers an alternative architecture targeting modern Postgres deployment patterns
  • Evaluate against PgBouncer for specific latency and throughput requirements
  • Consider resource overhead differences when migrating from established poolers
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AWS Database Blog awsdatabase

Automate PostgreSQL Audit Log Extraction to S3 via CloudWatch

AWS demonstrates a pipeline that captures PostgreSQL audit logs from CloudWatch Logs and converts them into structured CSV format. This automated workflow processes entries in near real time and stores the resulting files in Amazon S3. The approach enables long-term analysis of audit data without manual intervention.

  • Extracts audit logs from CloudWatch Logs automatically, reducing manual overhead.
  • Converts unstructured log entries into structured CSV for easier querying.
  • Stores data in S3 for scalable, long-term retention and analysis.
  • Operates in near real time, ensuring timely availability of audit records.
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PostgreSQL News database

PostgreSQL ODBC REL-18_00_0002 Fixes Stack Buffer Overflow and Includes OpenSSL 3.5.5

The PostgreSQL ODBC driver has released version REL-18_00_0002, addressing critical security and stability issues. Key updates include upgrading to OpenSSL 3.5.5 and patching a stack buffer overflow in getPrecisionPart(). The release also corrects SQLPrimaryKeys behavior for INCLUDE columns and adds validation for percent escapes in connection strings.

  • Upgrade immediately to patch a stack buffer overflow vulnerability in getPrecisionPart().
  • OpenSSL dependency is updated to version 3.5.5 for improved security posture.
  • SQLPrimaryKeys now correctly excludes INCLUDE columns, fixing metadata reporting.
  • Connection string parsing now validates percent escapes before decoding.
  • Resolves buffer read issues in conn_settings and ARD bookmark allocation failures.
CHECKLISTPostgreSQL ODBC Release NotesUpgrade immediately to patch stack buffer overflowUpdate OpenSSL dependency to version 3.5.5Fix SQLPrimaryKeys metadata reporting for INCLUDE columnsValidate percent escapes in connection strings
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