Operations | Monitoring | ITSM | DevOps | Cloud

Manage the full PostgreSQL database lifecycle from one AI-powered IDE. dbForge Studio for PostgreSQL brings together database design, development, and administration, as well as data management, analysis, reporting, and extensive automation. Additionally, the integrated AI Assistant generates, explains, optimizes, and troubleshoots SQL queries directly in the Studio. It supports on-premises PostgreSQL databases and related cloud services such as Supabase, Heroku, Amazon Redshift, and TimescaleDB.

Pat Wright sits down with PostgreSQL veteran Hari Kiran – founder of OpenSource DB and co-organizer of PG Day Hyderabad, where this episode was recorded. They talk community building, mentoring the next generation of PostgreSQL contributors, and how a coffee chat with a friend turned into one of India’s biggest PostgreSQL events.

This session walks SQL Server developers through a complete database development workflow, from designing schema changes to testing and deploying them safely, using SQL Toolbelt Essentials. Most database teams don't struggle with SQL itself. The friction comes from process: schema changes made without a clear picture of what's already there, inconsistent code quality across a team, databases left outside version control, and deployments that feel riskier than they should. This session covers all four, with a live demo in SSMS for each one.

PostgreSQL database development involves much more than writing and executing queries. Developers build applications, DBAs maintain database performance and reliability, analysts turn raw data into insights, and DevOps teams automate database delivery through CI/CD pipelines. In this video, you will see how dbForge Studio for PostgreSQL brings database development, management, data analysis, reporting, and automation into a single AI-powered PostgreSQL IDE.

AI can write database schema changes in seconds, but nothing should reach production until it's validated, tested, and approved. In this discussion, Ken Muse (GitHub), Steve Jones (Redgate), and Huxley Kendall (Redgate) show how a governed pipeline keeps AI-generated database changes safe without slowing teams down.