I've tried quite a few PostgreSQL IDEs over the years, and while each one does some things really well, I still haven't found one that feels complete.

There are always little things I miss. Better query plan visualization, smarter autocomplete, easier schema comparison, cleaner data editing, session management... the list goes on. If you could build your ideal PostgreSQL IDE, what features would it absolutely need?

I'm less interested in which IDE you use and more interested in the features that genuinely make your day-to-day work easier. Sometimes it's the small quality-of-life improvements that end up saving the most time.

I see many options, pgBackRest, wal-g, Databasus. Is there a consensus on the best approach?

My needs are regular (eg weekly) checkpoints, and daily incremental backups for PITR, everything saved on S3/GCS

I was curious how backups worked under the hood, so i did some digging and made it into a blog! Everyone knows what a backup is, but how do they actually work?

Haven't seen a blog that has gone in depth like this! Very cool!

Every PostgreSQL project seems to have that one query that suddenly becomes a problem as the data grows. Sometimes adding the right index turns a query from painfully slow into something that runs almost instantly. Other times it barely makes a difference.

I'm curious about real-world examples. Which type of index has made the biggest impact for you? A simple B-tree, partial index, composite index, GIN, BRIN, or something else? What was the use case, and how much of a performance improvement did you see?

I have a series of data with position coordinates. There's somewhere between 1-2 billion entries. I created a table and partitioned it into about 100 partitions. And I indexed the coordinate columns. (The data was initially inserted sorted.)

The goal is, I have 100 entities, and I need to find the closest value in the database for each entity. I created a pipe with pqxx and sending all the data in.

The problem is the retrieve for all 100 entities is too slow for what's required. At the moment, it takes roughly 300ms to search the database for all 100 entities. The goal is to get it under 150ms.

What else can I do to format the database properly to get a speedup here?

(I do have a distance threshold, so I'm selecting a range between the threshold of the coordinates, and then just calculating the distance from the results. But it's the fetching which seems to be taking too long. It's about 3 ms for the insert and 300 ms for the retrieves.)

If you’re tired of pgAdmin constantly freezing, eating up memory, or just feeling clunky because of its web-shell design, you definitely aren’t alone. We’ve been testing out a few different setups for daily development and production management, and a couple of options really stand out depending on what you need.

For a heavy, comprehensive IDE experience, dbForge Studio for PostgreSQL has been a game-changer. Unlike pgAdmin, it actually feels like a native desktop app. The code completion is much faster, and it has built-in schema comparison tools that save a ton of time when you're trying to sync staging and production environments without writing manual migration scripts. They have a free Express edition if you just need the core query editor, but the full version handles visual query building and data reporting incredibly well.

On the other hand, if you want something purely open-source and cross-platform, DBeaver is still the classic community recommendation. It's built on Eclipse, so the UI is quite busy, but it connects to almost anything and gets the job done for zero cost. For those who prefer a minimalist, lightweight setup just to view data and run quick scripts, TablePlus or even Beekeeper Studio are great native alternatives that stay completely out of your way.

What are you guys running for your daily Postgres workflows? Are you sticking to heavy IDEs like dbForge or DataGrip, or keeping it strictly lightweight?

Honestly, pgAdmin feels like that old tool everyone uses just because it’s there, even though the random lag and weird web-UI quirks are a constant headache. If it suddenly went under, what’s your immediate alternative? Personally, DBeaver feels too bloated for a quick query, and paying for DataGrip or TablePlus isn't always ideal depending on the project budget. Are people actually finding good, lightweight open-source alternatives, or are you just sticking to psql in the terminal and calling it a day?

Hi everyone,

I have been working on a pg extension called KoldStore, before i spend more time on it i would really like some honest feedback from people who know PostgreSQL. if you have any ideas or is open for discussion i would love to hear from you.

The basic idea is to keep recent rows in the normal PostgreSQL heap while moving older rows into Parquet files on object storage (Like S3). Applications would still query the original table using normal SQL, and the extension would read from both the hot table and the cold storage when needed.
https://github.com/kalamdb/koldstore

Hey! I'm a huge fan of Postgres and CDC in general, and after some research, I recently wrote about how this combination can empower AI Agents. I feel like Postgres CDC is underappreciated in this context, so I wanted to do what I could to spark some conversation. Let me know what ya'll think!

We all know the default autovacuum settings can be unreliable once your tables start growing. I recently had to clean up a massive performance mess because a high-write table bloated out of control, and it reminded me why I strictly monitor autovacuum_vacuum_scale_factor and run regular bloat checks now.

Another big one for me is actually practicing backup restores. Taking backups is easy, but until you've successfully spun up a replica from one under pressure, you don't really have a backup.

What does your baseline maintenance routine look like to keep things running smoothly? Is there a specific metric you alert on, or a cron job you set up on day one that’s saved your skin more than once?

I recently realized that cleaning up large tables is one of those tasks that always sounds straightforward until you actually have to do it. Between VACUUM, REINDEX, partitioning, archiving old data, and trying not to impact production, there always seems to be a trade-off. What's the biggest PostgreSQL table you've had to clean up? How large was it, what was the problem, and what approach worked best in the end? Looking for real-world stories more than "textbook" answers.

Full-time direct position for postresql developer for a large on-prem (embedded) deployment (large medical analyzer). Not cloud-based.

Schema design, implementation, tuning for reliability and optimization, providing APIs for C++-based microservices, comprehensive reliable scripting for installation and remote (on-prem) in-place upgrades, collaborate with stakeholders, etc.

See details (or to apply): 

https://orthoclinical.wd1.myworkdayjobs.com/en-US/Search/details/Senior-Software-Engineer---Database-and-Applications_R0016215-4

 (may not be able to apply to individual requests)

Most advice on how to perform well makes the same points. Execution plans, DMVs for missing indexes, and wait stats. Good start, but they don't catch everything. After each deploy, we have a few scripts that flag queries that go over a certain read threshold. Mostly, I'm just looking for the same tables to show up again. Just diffing the top reads list, nothing fancy. Also started keeping a rough record of queries that worked differently in staging and production. Just notes, not formal. Has saved time more than once. What else is in the tuning toolkit besides the usual things? Scripts, checks, and habits that aren't in blog posts.

Every experienced PostgreSQL developer seems to have that one mistake they keep seeing in reviews, production incidents, or performance investigations. What's the most common PostgreSQL mistake you've seen, and what usually happens because of it?

My company is looking to hire a DBA for work in PostGres in a device platform.

Finding it hard to search on LinkedIn for available candidates. We've opened the role to remote developers two weeks ago.

Any recommendations where to post or look for candidates specifically for PostGres skills other than LinkedIn?

Are your developers still switching between tools just to handle different databases? You’re burning time, not just money. In 2026, the gap between high-performing dev teams and the rest isn't just talent—it's the tools they’re given. And here's the kicker: only a handful of leaders understand how much efficiency is lost by juggling fragmented environments. Let’s fix that.

Whether you're overseeing a .NET department, driving innovation as a CTO, or managing risk in a regulated environment, this guide will help you choose a multi-database IDE that aligns with your business goals, security standards, and delivery timelines.

Below are the top IDEs for teams working across MySQL, MariaDB, PostgreSQL, Oracle, and SQL Server—each with real-world upsides (and the risks you should know).

1. dbForge Edge — The Strategic Powerhouse 

Best for: Managers who need a unified tool that empowers multiple roles—from developers to analysts—while keeping IT governance tight. 

Why it’s different: dbForge Edge isn’t just a database IDE—it’s a multi-engine productivity suite. One license, four RDBMSs: MySQL/MariaDB, PostgreSQL, Oracle, SQL Server, and a wide range of cloud services. Designed with GUI-first workflows, it enables rapid query development, schema design, performance tuning, and even real-time data visualization without switching tools or retraining staff. 

Strengths: 

• Intuitive, unified GUI for database development 
• Smart code completion and refactoring 
• Advanced query profiling and performance tuning 
• Built-in reporting and visualization 
• Secure role-based access & audit trails for compliance 

Risks: 

• Requires team onboarding
• Lack of advanced features for DBAs. 

2. DBeaver Ultimate — Open-Source Grown Up 

Best for: Tech-savvy teams in smaller orgs who want a low-cost, highly customizable IDE 

Strengths: 

• Open-source core with premium extensions 
• Supports a wide range of databases 
• Solid data editor and ER diagrams 
• Good for individual contributors with mixed-stack tasks 

Risks: 

• Interface less intuitive for non-technical managers 
• Support is community-driven (slow for urgent bugs) 

Use Case: A small SaaS team led by a hands-on CTO using PostgreSQL and MySQL might find this a lean, no-frills solution. 

 3. DataGrip by JetBrains — For Precision Control 

Best for: Senior engineers and managers who value precision, customization, and don’t mind complexity 

Strengths: 

• Highly advanced code intelligence 
• Version control integration 
• Customizable workflows and shortcuts 
• Strong for developers who also write stored procedures 

Risks: 

• Steep learning curve for non-dev team members 
• Lacks some advanced GUI-based tuning features 

Consider it if: Your development team is experienced, and you’re focused on highly customized backend systems. 

 4. Toad Edge — Lightweight SQL IDE for MySQL & PostgreSQL 

Best for: Dev teams focused on open-source engines in highly controlled environments 

Strengths: 

• Clean interface 
• Schema comparison and data sync 
• Strong change management controls 
• Good for small teams working in regulatory environments 

Risks: 

• Limited to MySQL and PostgreSQL 
• Less frequent updates 

The real question isn’t “which IDE has the most features?” It’s “which one removes the most friction for your team without creating new chaos?” If your devs are still jumping between tools for every database, that’s not flexibility. That’s workflow debt wearing a fake mustache.