Git for Data: Managing Data like Code with lakeFS

Is it possible to manage and test data like code? lakeFS is an open-source data version control tool that transforms object storage into Git-like repositories, offering teams a way to use the same workflows for code and data. In this episode, Kris sits down with guest Adi Polak, VP of DevX at Treeverse, to discuss how lakeFS can be used to facilitate better management and testing of data.At its core, lakeFS provides teams with better data management. A theoretical data engineer on a large team runs a script to delete some data, but a bug in the script accidentally deletes a lot more data than intended. Application engineers can checkout the main branch, effectively erasing their mistakes, but without a tool like lakeFS, this data engineer would be in a lot of trouble.Polak is quick to explain that lakeFS isn’t built on Git. The source code behind an application is usually a few dozen mega bytes, while lakeFS is designed to handle petabytes of data; however, it does use Git-like semantics to create and access versions so adoption is quick and simple.Another big challenge that lakeFS helps teams tackle is reproducibility. Troubleshooting when and where a corruption in the data first appeared can be a tricky task for a data engineer, when data is constantly updating. With lakeFS, engineers can refer to snapshots to see where the product was corrupted, and rollback to that exact state.lakeFS also assists teams with reprocessing of historical data. With lakeFS data can be reprocessed on an isolated branch, before merging, to ensure the reprocessed data is exposed atomically. It also makes it easier to access the different versions of reprocessed data using any tag or a historical commit ID.Tune in to hear more about the benefits of lakeFS.EPISODE LINKSAdi Polak's TwitterlakeFS Git-for-data GitHub repo What is a Merkle Tree?If Streaming Is the Answer, Why Are We Still Doing Batch?Current 2022 sessions and slidesSign up for updates on Current 2023Watch the video version of this podcastKris Jenkins’ TwitterStreaming Audio Playlist Join the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperLive demo: Intro to Event-Driven Microservices with ConfluentUse PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)

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Streaming Audio features all things Apache Kafka®, Confluent, real-time data, and the cloud. We cover frequently asked questions, best practices, and use cases from the Kafka community—from Kafka connectors and distributed systems, to data mesh, data integration, modern data architectures, and data mesh built with Confluent and cloud Kafka as a service. Join our hosts as they stream through a series of interviews, stories, and use cases with guests from the data streaming industry. Apache®️, Apache Kafka, Kafka, and the Kafka logo are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by The Apache Software Foundation is implied by the use of these marks.