Adam Szymański

Founder & CTO

Published
July 25, 2023

What is Oxla, and why you should care

tech preview

Hi All, we're Oxla - the world fastest distributed analytical database! We're excited to announce that we're on the eve of launching our public tech preview. This is a major milestone for us, and it wouldn't have been possible without the feedback from our community, and the hard work of our amazing team (thank you, thank you, thank you!). As we're on a mission to revolutionize data analysis – this preview is a huge step toward making that happen.

So...stay tuned because the launch is just around the corner!

What's Oxla, you ask?

At first glance, it is yet another OLAP database. You can insert the data, you can query it. It supports PostgreSQL wire protocol and a subset of PostgreSQL syntax. So why have we created it?

As users of analytical databases ourselves, we have encountered various challenges, including poor performance, high costs, scalability issues, complex data infrastructure, system crashes, and non-intuitive behavior. Therefore, we created Oxla in an attempt to address and solve these issues.

First of all, Oxla is extremely efficient. Most analytical queries run much faster on Oxla than on other solutions. It was not created to handle a single type of query, such as aggregates, but much more. It was also not designed to work with a specific data size; it can process simple queries running on a cluster within tens of milliseconds. Additionally, it can execute complex queries over large datasets by shuffling data through the cluster. It offers various variants of "group by" or "join" operations, depending on the data size and distribution. The best part is that you don't have to think about it; everything is done under the hood without your intervention. This means you will need fewer servers to process the data, you will be more productive while exploring your dataset, and you can use one solution to both serve real-time traffic and perform offline analysis.

Our solution also features a modern architecture focused on cloud deployment, with a decoupling of storage and compute. This design allows for easy scalability and enables the use of cost-effective and reliable storage solutions, starting with S3 and potentially expanding to include options like GCS, Azure Blob Storage, Ceph, HDFS, and more for on-premise deployments.

Oxla communicates using PostgreSQL protocol and uses its SQL dialect. Some people love it, some people hate it, but almost everybody knows it. That means it will be easy for you to start using Oxla. It also means that, most likely, the programming language you use is already able to communicate with Oxla using libraries like Psycopg or jackc/pgx. We are working on emulating more PostgreSQL internals to support more advanced tools: like Tableau or SQLAlchemy.

In short: we are presenting you the first step towards a solution that we wanted to use when working with data.

Now, what does this upcoming tech-preview release mean for you?

It means you'll have the opportunity to see what we have accomplished so far. We are aware that there is still a long road ahead, but if, after reading this text, you think Oxla might be suitable for you, give it a try. Register here to stay informed about the release, give Oxla a go, and contact us via email or join our Discord community to let us know your thoughts. If there are any missing features, please let us know. We are constantly working on prioritizing our roadmap, and we plan to make it public soon.

*Please notice that this tech preview will serve as an early release, offering a glimpse into the possibilities that will be introduced in the official, commercial multi-node Oxla version. However, it’s important to bear in mind that there might still be a few issues to address. Should you have any questions or encounter deployment challenges, please don't hesitate to contact us through Discord or via hello@oxla.com.

Give Oxla Cloud a spin

Try out Oxla Cloud with a 30-day trial and $200 in credits to experience the efficiency of its query engine using demo datasets or your own data.