DEVOURED
The most valuable API in the modern data stack returns no data
Data sharing is moving away from bulk API exports toward shared table references, enabling consumers to bring compute directly to object storage.
What: Bulk export APIs are being replaced by architectures utilizing Iceberg REST catalogs and object storage. By providing shared table references, producers allow consumers to access data without the overhead of pagination or redundant extraction pipelines.
Why it matters: This signals a structural shift in data sharing where the 'API' is essentially metadata, and the actual payload is moved through standard cloud storage primitives, reducing latency and infrastructure costs.
Deep dive
- Traditional APIs suffer from rate limits, serialization costs, and pagination overhead.
- Shared table references use metadata catalogs (like Apache Iceberg) to point to data in object storage.
- Consumers bring their own compute to the data, shifting focus from pipeline maintenance to data contracts and governance.
- Compaction and table maintenance become the primary responsibilities of the data producer in this model.
Decoder
- Apache Iceberg: An open-source table format for huge datasets that supports high-performance queries and evolution of data schemas.
- REST Catalog: An interface that manages table metadata via HTTP, allowing decoupled compute engines to access the same storage layer.
Original article
Bulk export APIs are giving way to shared table references. Iceberg REST catalogs, object storage, Parquet, and credential vending let producers publish metadata while consumers bring their own compute, avoiding pagination, rate limits, and duplicate pipelines. The hard parts move to contracts, compaction, semantics, privacy, and table maintenance promises.
Explore all 66 articles in today's digest
Fresh dev news, AI-digested daily. Never miss a trend at devoured.fyi