Hello folks, I've released new long awaited version (v1.4.0) of Cassandra/ScyllaDB driver with lot's of fixes and performance improvements.

https://github.com/he4rt/scylladb-php-driver

If someone is using the driver, please test it and report issues, or some feature requests. I'm now fully back on maintaining it regularly and improving it for the foreseeable future. Also wrote a blog post on my website explaining the changes done to the driver

https://www.dusanmalusev.dev/blog/scylladb-php-driver-140-the-extension-is-pure-c23-now

Finally, we have a Cassandra 4.0 beta!

Announcement -> https://cassandra.apache.org/blog/2020/07/20/apache-cassandra-4-0-beta1.html

Download -> https://cassandra.apache.org/download/

Datastax release post.

Change log.

Some new features:

• Triggers

• CQL Improvements

• Eager retries

Affiliation: I'm the maintainer of LibreDB Studio.

Shipped Apache Cassandra in 0.13.0; native CQL on 9042, probed against Cassandra 5.0.9 before the provider existed.

The thing I kept hitting in other browsers: they print a row count. Cassandra does not have one. system.size_estimates counts partitions in flushed SSTables, refreshed every 5 minutes, and on a clustered table it was 71% low. Printing 0 is the same lie with a different number. The table and storage panels here stay blank.

A few other refusals that are just the engine:

- no connection string (nothing in use carries localDataCenter, which the driver requires)

- no EXPLAIN (tracing is a profile of a finished statement, not a plan)

- no query cancel (the native protocol has no cancel frame)

- no invented table size from system_views.disk_usage (whole mebibytes)

ScyllaDB support is in-progress. Same wire, different system_views, untested, so unlisted.

Self-host:

docker run -p 3000:3000 libredb/libredb-studio

Every refusal named, with the measurement behind it:

https://github.com/libredb/libredb-studio/blob/0.13.0/docs/providers/cassandra.md

If you still live in cqlsh / DataStax Studio / DBeaver for Cassandra, what's the thing that still makes you open a terminal?

It also ships as a Helm chart, so it can sit in the same cluster as Cassandra instead of another desktop install. Browser, not Electron, a phone works, but that's a side effect of there being nothing to install.

Is anyone here using Astra in production these days? We are considering moving there as the price is right compared to licensing and infra for managing our current multi-datacenter cluster. While cassandra has been relatively easy to manage on VMs and quite stable, we're happy to offload that to a service if it's reliable. If there are any horror stories or good experiences from real-world production, I'd love to hear them.

If you're a developer or administrator who's looking to learn how to use the distributed NoSQL database Apache Cassandra, we (DataStax) has just recently launched free online self-paced training courses.

I recommend checking out DS101 first; it provides you with a nice overview of distributed systems and introduction to the open source Apache Cassandra database.

We have five additional courses that cover the topics of: Performance Tuning & Optimization, Data Modeling, Analytics with Apache Spark, and Search with Apache Solr; these can all be found at the link below.

Please visit the DataStax Academy self-paced courses page to get started: https://academy.datastax.com/courses/

I work with Cassandra quite a bit and wanted something more convenient than jumping between cqlsh and scripts for everyday inspection and data operations, so I built Kassandra.

It’s a web-based Cassandra client with:

• schema-driven browsing and CRUD

• raw CQL execution

• saved connection profiles

• local-datacenter selection / DC-aware routing

• Docker support

It’s open source and still evolving. I’d especially like feedback from people running Cassandra in real environments: what workflows would make a GUI like this genuinely useful for you?

GitHub: https://github.com/irajhedayati/kassandra

I’m currently thinking about features around cluster topology, query history, schema visualization and operational diagnostics, but I’d rather prioritize based on actual Cassandra users.

Interesting there are a couple of recent posts about Cassandra GUI tools.

I thought I would let you know about our AxonOps Cassandra Workbench, which is a mature Workbench product dedicated for Cassandra, built under Apache 2.0 License, available on Github, as an open source project.

It was built just before Claude, 😉by humans, and it continues to be developed for Cassandra, by Cassandra experts who have been working with the Cassandra community since 2008 - wow, time flies!

If anybody wants to get involved with the project, do let us know!

https://github.com/axonops/axonops-workbench

Like probably a few of us I stumbled upon a link through HN this week : http://www.scylladb.com/

The website indicates it's a C++ rewrite of Cassandra, and compatible with the original one at least for data structure, communication and other critical bits.

I have a very little experience with Cassandra and I am pretty happy about it, yet some things such as performance especially around compaction times was still a question mark for me.

Has anyone experimented with Scylla and checked their "supposed" improvements compared to Cassandra ?

Hi everyone,

I'm doing a small toy experiment with Cassandra and noticed something I wasn't expecting. I'm trying to understand whether this behavior makes sense or if there is something wrong with my experiment.

My setup is:

5-node Cassandra cluster, Replication factor (RF) = 3, All requests are read (100% read workload) with Consistency level = QUORUM, Total 2 million read requests. Object size is about 10KB

First, I ran the workload with all 5 nodes running and recorded the average latency.

Then, I stopped/killed one Cassandra node, leaving 4 nodes running. I ran the same workload again and noted the average latency.

Interestingly, the average read latency was lower with one node down than with all 5 nodes running.

Since RF=3 and CL=QUORUM, I understand that Cassandra needs 2 replica responses for a read, so a single node failure should still allow the reads to complete.

What I'm trying to understand is why the latency would actually improve after one node is down.

Could this be related to:

* replica selection or coordinator selection changing after the failure?

* Cassandra avoiding a slower replica/node?

* differences in cache/page-cache state?

* some other aspect of the read path?

I'm mainly interested in understanding what Cassandra is doing internally in this situation. This is just a small experimental setup, so I'm also wondering if there are particular things I should measure to make the comparison meaningful.

Thanks!

In 2023 Discord migrated from using Cassandra to scylladb. I’m wondering if there was a response by the Cassandra team or developer ?

Context: https://discord.com/blog/how-discord-stores-trillions-of-messages

I've spent a lot of years operating Cassandra clusters, and one thing that still surprises me is how much DIY platform engineering you end up doing just to run it well.

The database itself is fantastic. But the operational side often looks something like:

• Prometheus scraping some of Cassandra's JMX metrics

• Grafana dashboards someone copied from somewhere

• nodetool scripts for repair

• custom backup jobs

• random shell scripts that only one person understands

• a bunch of tribal knowledge about what metrics actually matter

It works, but it also means every team ends up rebuilding their own Cassandra operations stack from scratch.

We ran into exactly this problem ourselves running clusters, so we started building AxonOps to solve the operational side of Cassandra. The idea was basically: what if Cassandra actually had a proper control plane instead of a pile of scripts?

Some things we focused on:

• high-resolution metrics that actually let you see what's happening inside the cluster

• automated repair management

• backups and point-in-time recovery

• troubleshooting tools that understand Cassandra instead of generic monitoring

• operational workflows built around how Cassandra actually behaves

Not trying to replace Cassandra tooling or the ecosystem, just trying to make the operating Cassandra at scale part less painful.

I'm genuinely curious what people here are using these days.

Are most people still running the Prometheus/Grafana + scripts setup?
Using managed services like Astra or Keyspaces?
Or have people built their own internal tooling platforms?

Would be interesting to hear what setups people are running in production.

I am new to this sub and new to cassandra. I am working on migrating my application from 100% MySQL to mostly cassandra. I met with Datastax today to view their product, and it looks nice, tailored to free me from management and focus on development. In price comparing, I came across AWS Keyspaces. I can't find much about it in terms of a demo, but if I understand correctly, it is and the AWS calculator shows that it is almost the same price as Astra DB.

So my question is for anyone with experience with one or both, what is the direction you went with and why? We are in the AWS space already with EC2 and S3, and when we go live, we look to scale to other regions as well.

Thanks in advance

➡️ October 22, 2025
➡️ Please Join Us!
🔥The Apache Cassandra® New York Metro Area User Group🔥

Impactful Presentations:
- Future of Cassandra® based GenAI with IBM Watsonx
- ACID Transactions with Apache Cassandra (Aaron Ploetz)
- Performance Improvements & Upgrade Challenges: Bloomberg’s Road to Apache Cassandra 5.0
(Andrés Beck-Ruiz William Nguyen)

Sign Up Here: https://luma.com/98j1utv6

Networking 🔗 , refreshments 🍕, SWAG and all things Cassandra!

Hey all, 5.0.4 was just released and it includes a big storage engine optimization that I worked on with fellow committer Jordan West. We found a way to significantly improve the way we handle IO to get a big improvement in compaction throughput. This post takes a look at the low level details of how things work, the improvement, and some other improvements on the horizon.

Tomorrow, I'm starting another data modeling series that assumes starting with version 5. The last time I did something this comprehensive was for Cassandra 3. Needless to say, there have been a LOT of updates since then.

There will be five parts and each one has its own signup for the live stream:

• Foundations of Cassandra Data Modeling (April 8) - Learn the query-first design approach that will form the basis of all your Cassandra data models

• Advanced Query Patterns (May 6) - Master SAI to simplify complex access patterns without sacrificing performance

• Data Types and Enhanced Functions (June 3) - Implement vector search and enhanced functions for sophisticated content recommendation systems

• Data Protection and Governance (July 1) - Design robust data protection mechanisms that satisfy regulatory requirements without compromising user experience

• Migration Strategies - Cassandra 3.x to 5.0 (July 29) - Apply proven migration strategies to modernize your existing Cassandra implementations

If you miss the 9AM PT live stream, you can click on the link later, and signing up will give you instant access to the replay. I will be taking questions in the live stream. Feel free to drop a question in this thread as well.

As a bonus, you’ll get a Certificate of Completion for Cassandra Data Modeling 2025 if you sign up for all the sessions.

See you online!