Category: Advanced (300)

How CORTO scaled Amazon Aurora PostgreSQL with pgvector to 7.6 billion vectors and 2.5 billion documents in production, delivering sub-second legal search for 10,000+ law firms at 75% lower storage cost.

Channel Corporation shares how they split their all-purpose Amazon DynamoDB User table into role-specific tables, moving Badge data into a dedicated UserBadge table to stop transaction-conflict throttling and GSI back pressure, and how they ran a zero-downtime online migration using DynamoDB Export and Import with Amazon S3 and AWS Glue.

If you need cross-database access on Amazon RDS for SQL Server but cannot enable TRUSTWORTHY, module signing with certificates is the secure, RDS-compatible alternative. This post shows how to grant cross-database permissions to specific stored procedures without TRUSTWORTHY and with a stronger, least-privilege security posture.

Migrating full-text search from SQL Server to PostgreSQL can silently change results because the engines handle text, linguistics, and accents differently. This post shows how to reproduce SQL Server full-text search on Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL, covering collation, tokenization, accent-insensitive search, and synonyms.

PostgreSQL out-of-memory (OOM) events and excessive disk spilling are among the most common production incidents on Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL. Learn how PostgreSQL allocates and consumes memory, how to identify memory-intensive queries, and how to diagnose, prevent, and recover from OOM events on both engines.

Oracle Database@AWS places Oracle Exadata infrastructure inside AWS data centers, so SQL*Net latency between your application and the database can change after migration. This post presents the CRET methodology, a three-phase approach using AWR, Active Session History, and SQL Trace, to identify latency-sensitive SQL and quantify the impact before you migrate.

Learn how to use binary quantization with reranking (HNSW+BQ) in pgvector to scale vector search to hundreds of millions or billions of vectors on Amazon Aurora PostgreSQL, with practical guidance on index sizing, recall validation, and the scenarios where the approach works best.

Learn how to configure Oracle Materialized Views with Fast Refresh and materialized view logs to enable efficient, incremental AWS DMS change data capture (CDC) replication. This approach eliminates full-reload overhead and achieves near real-time migration of large, multi-table joined views to AWS.

Stream Amazon Aurora DSQL change data capture (CDC) events into Apache Iceberg tables on Amazon S3 with Amazon Data Firehose, then query them using Amazon Athena. This post walks through a two-table design that keeps a full audit trail and a current-state view, plus deployment and a dashboard for exploring the results.

Learn how to use Oracle SQLcl, a lightweight alternative to the full Oracle Client, to create and manage an Oracle Wallet for SSL connections between AWS DMS and Amazon RDS for Oracle. This post walks through installing SQLcl, adding certificates, testing the SSL connection, and configuring the AWS DMS endpoint.