databloks

Databloks is a modular data storage and processing paradigm that organizes data as reusable, self-contained units called blocks. Each block encapsulates a defined data structure and its metadata, enabling independent storage, versioning, and governance. Blocks are designed to be composable, so datasets or data products can be assembled by linking relevant blocks rather than duplicating data.

Block types commonly described within the Databloks concept include DataBlocks, which hold the actual records; SchemaBlocks, which describe the structure and constraints of the data; Reference or LinkBlocks, which establish relationships between blocks; and Metadata or ProvenanceBlocks, which record lineage, quality metrics, and access controls. A central block registry or catalog tracks versions, lineage, and dependencies, while blocks themselves may reside in object stores or distributed filesystems.

The architecture emphasizes immutability, modularity, and governance. Data is ingested into blocks or materialized from existing blocks, and transformations produce new blocks that reference prior ones. This enables clear data lineage, traceability, and rollback capabilities. Access controls and policy enforcement can be applied at the block level, supporting governance across large data ecosystems.

Usage patterns include designing blocks to reflect real-world concepts (entities, attributes, relationships), composing blocks into datasets or data products, and employing block pipelines to transform or enrich data without altering source blocks. Querying and analytics can span multiple blocks through defined relationships or materialized views, while metadata and versioning support reproducibility and audits. Databloks are positioned as a approach to modular data architecture in data engineering and analytics contexts.