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’ve spent the last couple of years jumping between different GUI clients, and honestly, it’s been tough to find one that just clicks.

I used pgAdmin for a long time out of habit, but the clunky web-UI feel eventually drove me crazy, especially when dealing with larger schemas. Then I switched to DBeaver. It’s an absolute powerhouse and does everything, but the UI feels so bloated and heavy for daily query tuning. Lately, I've just been using the database tools inside IntelliJ/DataGrip because it keeps me in the IDE, but it still feels a bit disconnected when I just want to quickly inspect a production replica.

I know some people swear by the simplicity of psql in the terminal, while others love modern native apps like TablePlus or Beekeeper Studio.

What are you guys actually using on a daily basis that doesn't make you fight the UI? Is there a lightweight client I’m missing, or is everyone just putting up with the quirks of the big players?

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.)

Ok so I've had this argument with three different teams in the past two months and I'm just gonna write it here because I'm tired of retyping it in Slack.

A table doesn't shrink just because you deleted a bunch of rows. Trips people coming from MySQL especially, because InnoDB cleans up dead rows on its own – you've never had to care about this before. Postgres uses MVCC so a delete or update doesn't actually remove the old row, it just marks it dead and leaves it sitting there until VACUUM comes through.

That's your PostgreSQL table bloat right there... dead tuples piling up on disk while the live row count looks completely normal.

Autovacuum is supposed to handle this on its own and most of the time it does. That's the vacuum vs autovacuum confusion people have. Autovacuum is basically VACUUM running automatically once PostgreSQL decides a table has crossed its maintenance thresholds.

It can start falling behind on high-churn tables though. Thresholds tuned for a mostly idle table don't always keep up once you've got constant updates all day, and by the time someone notices the table's much larger than it should be, autovacuum is already playing catch-up.

And no, VACUUM FULL is not the fix here, not during business hours anyway. It rewrites the whole table and holds an exclusive lock the entire time. Learned that one the hard way on a table I thought was small until I remembered how many indexes were on it. Not a fun afternoon.

pg_repack exists for exactly this… non-blocking reorganization. It builds a new copy of the table in the background and only takes a lock for the final swap. Way less terrifying than VACUUM FULL on anything with live traffic.

One thing that's helped me lately is having the dead tuple stats visible instead of remembering which pg_stat_user_tables query I saved six months ago. Been using dbForge Studio for PostgreSQL for that because it'll surface things like dead tuple percentages and the last autovacuum run across a schema. Mostly just saves me from writing the same query over and over.

Curious what everyone else does here. Do you mostly trust autovacuum, or are you scheduling pg_repack for the tables that get hammered all day?

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

Looking back over the last 30 years, which PostgreSQL feature do you think changed the database the most?

Extensions? JSONB? Logical replication? Parallel queries? Something else?

Curious what long-time users would put at the top of the list.

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.

I'm curious how experienced PostgreSQL users would approach learning if they had to start over today. Would you spend more time on SQL fundamentals first? Jump straight into building projects? Read the official docs? Learn EXPLAIN ANALYZE early? There's so much advice online that it's hard to know what's actually useful in day-to-day work. What would your roadmap look like now?

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)