License? It doesn't seem to be open sourced.
Do you anywhere elaborate what you mean by leaderless, and how this affects the semantics and guarantees you offer?
So far as I understand both Kafka and Pulsar use (leader-based) consensus protocols to deliver some of their features and guarantees, so to match these you must either have developed a leaderless consensus protocol, or modify the guarantees you offer, or else have a leader-based consensus protocol you utilise still?
From one of your other answers, you mention you rely on Apache Bookkeeper, which appears to be leader-based?
I ask because I am aware of only one industry leaderless consensus protocol under development (and I am working on it), and it is always fun to hear about related work.
I’m the co-founder of EloqData. I recently gave a talk on EloqDoc and Pulsar integration at Data Streaming Summit 2025. It was a great event, and Ursa was definitely one of the hottest topics discussed.
I believe object storage is shaping the future architecture of cloud databases. The first big shift happened in the data warehouse space, where we saw the move from Teradata and Greenplum to Snowflake accelerate around 2016. Snowflake’s adoption of object storage as its primary storage layer not only reduced costs but also unlocked true elasticity.
Now, we’re seeing a similar trend in the streaming world. If I recall correctly, Ursa was the first to GA an object-storage–based streaming service, with Kafka(WarpStream) and AutoMQ following afterward.
I also believe the next generation of OLTP databases will use object storage as their main storage layer. This blog post shares some insights into this trend and the unique challenges of implementing object storage correctly for OLTP workloads, which are much more latency-sensitive.
https://www.eloqdata.com/blog/2025/07/16/data-substrate-bene...
Was the key unlock here the ability to append data to an object?
(https://aws.amazon.com/about-aws/whats-new/2024/11/amazon-s3...)
Ursa published a blog post saying their leaderless, stateless, object storage–based Kafka replacement can reduce costs by up to 95%. Has anyone here tried Ursa in production? How much cost reduction have you actually seen compared to Kafka or MSK in real workloads?
To me it seems Pulsar, a stream native sponsored project has not picked up. So a wrapper over Kafka/Pulsar with all Kafka compatibility and perhaps pulsar technology in cloud streaming engine is good business play.
How does it compare to AutoMQ? (https://github.com/AutoMQ/automq)
Has anyone tried Ursa before? Curious to hear your thoughts!
How is it different to bufstream?
Congrats on the launch! This is Zhenni from PuppyGraph. Shameless plug - We recently supported Ursa and here is the joint blog to showcase how to integrate Ursa engine with PuppyGraph to enable real-time graph analytics for a financial service use case with data stored in a lake house (not graphDB): https://streamnative.io/blog/integrating-streamnatives-ursa-...
Lets hope that you guys open source this in a great manner and actually still live really nicely.
If I may ask a philosophical question, when would you consider your product to "succeed", would it be when someone uses it for something important or some money related benchmark or what exactly
Wishing Ursa team peace and success. maybe don't ever enshittify your product as so many do. Will look at you from the sidebars since I don't have a purpose to even kafka but I would recommend having some discord or some way to actually form a community I suppose. I recommend matrix but there are folks who are discord too.
Anyways, have fun building new things!
If it's not open-source or at least self-hosteable I don't think it will be that useful
Just share a blog post published before, which compares the costs of running a 5 GB/s Kafka workload using Ursa, Warpstream, MSK, and Redpanda:
https://streamnative.io/blog/how-we-run-a-5-gb-s-kafka-workl...
And the test result was verified by Databricks: https://www.linkedin.com/posts/kramasamy_incredible-streamna...
The analysis in the blog is based on two key assumptions:
- Multi-zone deployment on AWS - Tiered storage is not enabled
If you’re looking to estimate costs with tiered storage, you can ignore the differences in storage costs mentioned in the post.
One important point not covered in the blog is that Ursa compacts data directly into a Lakehouse (This is also the major differentiator from WarpStream). This means you maintain only a single copy of data, shared between both streaming reads and table queries. This significantly reduces costs related to:
- Managing and maintaining connectors - Duplicated data across streaming and Lakehouse systems