Babelfish for AWS Aurora PostgreSQL - Hands on Learning

Explore Babelfish in Aurora Postgres, its features, including single and multi DB, and build a Babelfish cluster in AWS console, connect via SSMs or SQL Server Management Studio.

Discover how Babelfish enables migration from SQL Server to open source by using a PostgreSQL database that understands T-SQL, offering dual endpoints for SQL Server and PostgreSQL.

Explore Babelfish implementation on AWS Aurora Postgres, with two endpoints for T-sql and Postgres queries, and learn how it accelerates migration and provides development model guidance.

create a babelfish cluster in the aws rds console by selecting aurora postgres compatible and enabling the babelfish extension to support t-sql, in dev and test.

Connect to the babelfish cluster from SQL Server Management Studio using the endpoint and choose writer endpoint for read-write or reader endpoint for read-only, then verify version 3.2 and 15.3.2.

Learn the steps for migrating Babelfish, using the compass tool to generate and analyze reports, apply modified scripts to the Babelfish cluster, and migrate data with AWS DMs service.

Configure a migration architecture that connects a SQL server on EC2 or on prem to a Babelfish cluster via the DMS replication instance, with security groups controlling access.

Learn step-by-step migration from a commercial SQL server to Babelfish on AWS Aurora PostgreSQL, including Compas report generation, schema conversion, data migration with DMS, and application reconfiguration.

Download and install the compas tool for Babelfish, verify 64 bit Java JRE 8 or later, unzip the GitHub zip to the Babelfish binaries folder, and run Babelfish compass --help.

Download and install Java JRE 8, set the PATH, and reboot; download and extract the Babelfish compass tool from GitHub, then verify installation with a cmd test command.

Learn to generate composite reports using Babelfish compass, export DDL from SSMs, and view dependency reports with the xref option to map object relationships.

Generate a Babelfish compass report with dependency rewriting to auto-convert some DDL. It outputs an HTML file and a rewrite folder, and delete lets you reuse the report name.

Navigate to the Babelfish compass directory, run the compass command to generate an HTML report from DLLs, and use delete, xref, or rewrite options to customize outputs.

Analyze compass report details by reviewing the CSV and HTML outputs, focusing on non-supported features, complexity, and suggested workarounds to plan migration from SQL Server to Babelfish.

Verify Babelfish and Aurora PostgreSQL versions, configure escape hashes to ignore unsupported features, create the Northwind database on Babelfish, and map PostgreSQL schemas for AWS DMS data migration.

Learn how to migrate from SQL Server to Babelfish on AWS Aurora PostgreSQL by handling non-supported features, applying bytea workarounds for image data, and loading tables with only primary keys.

Migrate data into a Babelfish cluster using multiple methods. The preferred method is DMS, with a Postgres endpoint; other options include native scripting, SSIS packages, and BCP.

Learn to migrate data with DMS by configuring a replication instance, defining source and target endpoints for SQL Server and Babelfish, and building a replication task to move data end-to-end.

Explore how to set up an AWS DMS replication instance, define endpoints, and connect a SQL Server source to a Babelfish cluster using a replication task.

Create and test AWS DMS endpoints to connect a SQL Server source (Northwind) to a Babelfish DB target, configure credentials, and verify connectivity.

Create an aws dms replication task linking source and target endpoints, apply a selection rule and a transformation rule to lowercase names for babelfish on aurora postgres, and monitor progress.

Complete next steps after migrating to a Babelfish cluster by creating remaining indexes, validating code objects via the compas report, adapting sql server features to Postgres, and testing.

Download the compas tool from GitHub, unzip it, ensure JRE 8 or higher, and generate reports (basic, xref, dependency rewrite) to load data from Microsoft SQL Server to Babelfish.

Explore the different ways to monitor a Babelfish cluster and compare the options. See a quick console demo showing how to monitor Babelfish from the console.

Enable CloudWatch monitoring by default for RDS, including Babelfish, to track metrics such as CPU utilization, DB connections, and IOPs from hypervisor, but it misses slow queries and OS-level metrics.

Enable enhanced monitoring to have AWS install agents on the DB instance, delivering metrics up to one second granularity and CPU usage by processes and threads, with a nominal charge.

Learn how performance insight provides granular database metrics beyond CloudWatch, revealing slow queries, user activity, and blocking; use the Performance Insights dashboard to identify and tune slow queries for performance.

Explore performance insights for a rds aurora postgres instance with the performance insight dashboard. Track average active sessions (aas) to gauge load and spot bottlenecks when aas exceeds cpu.

Learn to monitor a babelfish cluster in the RDS dashboard using CloudWatch metrics, enhanced monitoring, and performance insight. Discover CPU utilization, memory, load, and Top SQL insights for diagnosing slowness.

Recap the Babelfish cluster monitoring options: CloudWatch's free metrics, enhanced monitoring with one-second granularity, and Performance Insight for query behavior; note charges for enhanced monitoring and Performance Insight.

Explore performance tuning in Babelfish for AWS Aurora PostgreSQL using the performance monitor and the Babelfish statistics profile to identify slow queries, view the query plan, and optimize with indexing.

Explore backup and restore methods for Aurora, including automated and manual backups, and use the AWS backup service to automate the process, then restore backup into a new Aurora cluster.

Automatic backups for Babelfish and Aurora clusters use incremental backups retained for your retention period, restore to any point up to retention window, and create a new cluster when restored.

Take manual snapshots of Babelfish or Aurora clusters via console, CLI, or API; they persist after cluster deletion and require separate storage fees, and restoration creates a new cluster.

Explore how AWS Backup Service centrally manages and automates backups for all AWS services, including Aurora and Babelfish clusters, with scheduled backups, configurable options, and tag-based checks.

Explore backup and restore workflows in Babelfish on Aurora, including automatic and manual snapshots. Discover point-in-time recovery and create a clone for testing without storage impact.

Automated backups are enabled for Babelfish or Aurora clusters; restoring from backups creates an Aurora cluster. Manual snapshots persist after deletion, incur charges; AWS Backup automates incremental backups and restores.

Develop practical skills in Babelfish for AWS Aurora PostgreSQL, from foundations to hands-on migration. Migrate a simple SQL Server database like AdventureWorks and review AWS docs for features and updates.

Conclude the hands-on learning journey with Babelfish for AWS Aurora PostgreSQL, emphasizing practical setup and usage insights.