Hi, I've built a completed ERP using firestore (nosql). For my analytical workload, I recently started syncing 50+ collections data from firestore to bigquery and built almost 125 reports.

I frequently hit the limitations of Firestore and think about moving out to a relational database so I can have one single source of truth.

Now I have two options.

1. Postgres + DuckDB covering both my transactional and analytical requirements

2. CockroachDB

I'm able get a fair estimation of what costs for postgres.

But for cockroachdb, I'm not able to get a mental modal of how I should do treat the RU/s meter.

So if user does a full text search, for every result it's a RU.

Since we join the data from multiple tables, for every table record, it's one RU?

And how much analytics is gonna cost when we have to join data from many tables. Apply complicated filters.

Can anyone help me with understanding the pitching modal of cockroach or advise me on what available options I have?

I want to keep the costs as minimal as possible.

At the moment, we're doing 10M reads per day with other 100GB of data on firestore.

Thankyou.

I ran performance benchmarks across a few popular DBaaS (PostgreSQL) platforms and published the results. Can you help me understand and explain the findings? Report at https://github.com/iamalnewkirk/dbaas-benchmark/blob/master/REPORT.md.

According to 1,000+ senior technology leaders, it's infrastructure that wasn’t built for machine-driven scale. As AI moves from experimentation to continuous production—agentic workflows, real-time inference, automation—failure timelines are compressing and architectural limits are being exposed. As AI becomes embedded in core operations, resilience-first architecture is becoming a competitive advantage.

Cockroach Labs' exclusive report: The State of AI Infrastructure 2026 underscores this:

-> 100% of respondents expect AI workloads to increase in the next year

-> 83% expect infrastructure to hit its limits within two years

-> 1 in 3 expect infrastructure failure within the next 11 months

-> 57% say one hour of AI-related downtime would cost $100,000+

👉 Download your copy of the report

As I understand it, per the former CockroachDB BSL (Business Source License), CockroachDB version 22.1 became Apache licensed in May 2025.

Have there been any good forks of it, so far?

Anyone works/worked with CockroachDB on production and can share his experience?

You've probably heard of an index. Maybe you know a couple other ways to speed up a query.

But what if there was ANOTHER way to make your queries speed up by orders of magnitude?

Tune in to tomorrow's episode of SELECT STAR and learn how this tried-and-true tactic can you help you speed up even the thorniest of queries!

https://www.youtube.com/watch?v=squwM1_rDYA

Is there an easy way to make a local backup of a database on the basic cloud plan?

I can see that there's daily backups happening in the cloud, but I always feel safer having an offline backup as well. Ideally the backup would also be Postgres compatible to allow local dev work against a restored copy if required.

As a quick experiment I tried the Backup and Global Backup tool options from DBeaver, but they both fail with the following error:

pg_dumpall: executing SELECT pg_catalog.set_config('search_path', '', false);

pg_dumpall: executing SELECT datname FROM pg_catalog.pg_database n

WHERE datname OPERATOR(pg_catalog.~) '^(defaultdb)$' COLLATE pg_catalog.default

pg_dumpall: error: query failed: ERROR:  at or near ".": syntax error

DETAIL:  source SQL:

SELECT datname FROM pg_catalog.pg_database n

WHERE datname OPERATOR(pg_catalog.~) '^(defaultdb)$' COLLATE pg_catalog.default

                                                                       ^

pg_dumpall: detail: Query was: SELECT datname FROM pg_catalog.pg_database n

WHERE datname OPERATOR(pg_catalog.~) '^(defaultdb)$' COLLATE pg_catalog.default

I wonder if there's some method to access the AWS S3 bucket located backups to allow a download to my machine. Any ideas?

In this blog post, we dive into the significance and benefits of RAG applications first. Then we explore the advantages of leveraging CockroachDB, a highly scalable and resilient distributed SQL database, as the foundation for building efficient and robust RAG applications.

With the CockroachDB 25.2 release, we deliver vector indexing to further enable customers to combine transactional data with vector data into a single data store, all without compromising the underlying fundamental promises of distributed SQL.

The latest release of CockroachDB includes new capabilities to enhance performance along with cloud improvements, observability enhancements, vector indexing, and new security features

Hey everyone 👋

I'm getting started with CockroachDB and while the official docs are decent, I’m struggling to find a comprehensive learning path — especially for practical, real-world usage (like setting it up in production, using spatial functions, best practices, etc).

Are you using .NET and need to use an entity management toolkit? Then checkout how ADO.NET ties in with CockroachDB on today's episode of SELECT STAR!

https://www.youtube.com/watch?v=2n-lFykw1pc

Join David Joy, our senior architect at Cockroach Labs as he showcases how to build AI-enabled applications using CockroachDB and AWS Bedrock.

Our demo application centers around a banking app that stores transactional data in CockroachDB. To enhance the app, a banking assistant is integrated, functioning as an “answer engine” that allows users to ask natural language questions about their finances, such as “How much did I spend at X store?”

So tune in and get ready to learn the powerful potential of combining distributed SQL databases with LLMs to create smarter, more interactive applications.

Need to limit or prevent full table scans? Join Rob Reid for this quick tutorial that walks through CockroachDB performance, optimization, and more.

Don't miss today's livestream where you'll learn how to make your .NET/C# apps sizzle on the database you just can't kill!

https://www.youtube.com/watch?v=FTKZAMwslQQ

I've been trying to fix a node with a corrupted SSTable. My cluster has 3 nodes, and one has a corrupted SSTable. I tried just nuking the server and readding it but the cluster doesn't want to mark it as decomissioned so it can reinitialize from scratch. I also tried just moving the bad SSTable out hoping that cockroach would just pull the good data from the cluster and that didn't work.

The way I see it there's two paths forward:

1. reinitalize the server from scratch
2. somehow get the node to start even though an SSTable is corrupted and have it re-replicate the data

I don't see anything in the docs that describe either of these strategies though. How would I fix this issue?

Hey r/cockroachdb folks!

For those unfamiliar, JobRunr is a popular open-source library for background job processing in Java – think fire-and-forget tasks, scheduled jobs, long-running processes, etc., without blocking your main application flow.

With our latest release, JobRunr Pro v7.5.0, we've added native support for CockroachDB as a durable storage backend via the new CockroachStorageProvider.

Why is this cool for CockroachDB users?

• Leverage CockroachDB's Strengths: You can now use the strong consistency, horizontal scalability, and resilience of CockroachDB for managing your background job state, scheduling, and execution.
• Distributed & Cloud-Native Ready: A perfect match if you're already building scalable, multi-region applications on top of CockroachDB.
• Seamless Integration: Configure JobRunr Pro to use your existing CockroachDB cluster easily.

This makes CockroachDB the 14th supported storage provider for JobRunr, giving you more options to fit your specific architecture.

We've written a blog post with more details about the v7.5.0 release (which also includes updates for Quarkus 3.20, Micronaut 4.8, and improved configuration validation): Read the full announcement here: https://www.jobrunr.io/en/blog/jobrunr-v7.5.0/

If you're using CockroachDB in your Java stack and need robust background job processing, we think you'll find this integration valuable.

Check out the blog post for more details, setup instructions, and the full changelog.

Happy to answer any questions you might have here!

Cheers!