Cost-effective data.

Big data adds significant value to your organization but can also add significant cost. Buoyant Data specializes in improving data infrastructure with high performance low-cost ingestion and transformation pipelines with Rust, Python, Databricks, and AWS.

Let's improve the ROI of your data platform!

Contact us

Delta Lake Support

As creators of the deltalake Python and Rust packages, we have been supporting Delta Lake applications since the beginning. Buoyant Data offers one-time on-demand support as well as on-going technical support subscriptions for your team!

Rust Development

With years of experience creating and deploying Rust data applications with delta-rs, kafka-delta-ingest, and more, Buoyant Data can help your organization adopt and excel with high-performance, low-cost data services or AWS Lambdas built with Rust.

Data Architecture Consulting

Our expertise in leveraging Delta Lake includes both the Databricks Platform (Serverless, Unity, etc) and the AWS Data Platform (Glue, Athena, EMR). We can help design and implement a scalable and efficient data platform for your organization.

Infrastructure Optimization

For organizations with existing data infrastructure and analytics, we can analyze and optimize in-place to squeeze faster queries and lower costs out of your existing data platform without substantial rearchitecture.

Introducing

Delta Lake: The Definitive Guide

Expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data. You'll also uncover how ACID transactions bring reliability to data lakehouses at scale.

Recent Posts

The buoyant_kernel distribution

The next version of Delta Lake for Rust and Python will use a tailored distribution of delta_kernel. The new buoyant_kernel allows features, bug fixes, and optimizations to ship to users faster than before.

Investing in Delta Lake Security

The recent supply-chain attacks in the Python ecosystem has shaken the confidence of a number of organizations who depend on Python to power their data ecosystem. In this post we detail how Buoyant Data is helping to ensure the security of the Delta Lake project.

Triggering small ETL workloads

Processing less data is the best way to reduce data platform costs. The key is to use event-driven pipelines rather than scheduled pipelines to only process data when it is ready!