Big data adds significant value to your organization but can also add significant cost. Buoyant Data specializes improving data infrastructure with high performance low-cost ingestion and transformation pipelines with Rust, Databricks, and AWS.
Our expertise in leveraging Delta Lake, Databricks (including Unity catalog), and AWS Glue or Athena can help design and implement a scalable and efficient data platform.
At a protocol level Delta Lake can scale to an infinite number of concurrent readers and writers, in theory, so long as the underlying storage provider supports strong atomicity. On AWS the Simple Storage Service lacks a necessary "put if absent" operation which requires Delta writers coordinate to ensure consistent writes to any given table.Read more
Remove those pesky hard-coded secret keys from your data applications and learn how to assume roles using built-in credential providers in AWS. This post includes examples that can be copied for both Rust and Python applications which need to access Delta tables.Read more
Optimizing cost of workloads running on Databricks can be daunting at first, but there are plenty of low hanging fruit! These tips will help you save thousands of dollars annually on your big data's big bills!Read more
Buoyant Data will be in San Francisco for Data and AI Summit from June 26th to June 29th. We'll be talking about alternative data pipelines using Rust and Python, and cost optimization in AWS. Come find us!Read more
A developer focused post explaining how to write to a Delta table in Rust using the Apache Arrow RecordBatch data structure.Read more
Discussing whether it is possible to have a Databricks deployment with a $0 idle cost in AWS. It is a nice idea, but not entirely possible in practice. This post discusses the minimum footprint possible with Databricks.Read more