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️ AI Assistants & ️ Data Ops: PyData Heilbronn #1 @ IPAI
Discover how LakeFS enables data version control and rollback with a data lake, ensuring traceability, auditability, and reproducibility, and learn about its features, including transaction support, commit history, and multiple cloud support.
- Data version control is the process of systematically tracking different versions of datasets to ensure traceability, auditability, and reproducibility.
- LakeFS is an open-source project that enables data version control and rollback with a data lake.
- LakeFS does not work like Delta Lake, which only stores diffs, but instead detects files that have been changed and copies those.
- LakeFS is designed to be a safe and reliable way to store and manage data, with features such as transaction support and commit history.
- The LakeFS spec is used to interface with the LakeFS file system and provides a file system interface for working with versioned data.
- LakeFS supports multiple clouds, including AWS, Azure, and Google Cloud, as well as on-premises storage.
- LakeFS provides transaction support, which ensures that changes to data are atomic and can be rolled back if needed.
- The LakeFS spec is used to automate the discovery of authentication credentials and provides support for file system operations such as reading, writing, and committing data.
- LakeFS provides a familiar Git-like interface for versioning data, with features such as committing, tagging, and reverting changes.
- LakeFS can be used for large-scale datasets, with a maximum size of one terabyte per file.
- The LakeFS spec provides support for caching, which can be used to reduce the amount of data that needs to be transferred over the network.
- LakeFS provides a way to reference previous versions of data, using commit IDs and tags.
- The LakeFS spec provides a way to automate data version control, using features such as transaction support and commit history.
- LakeFS supports multiple data formats, including CSV, JSON, and Parquet.
- LakeFS provides a way to version code and data together, using a single version control system.