Inputsto

Inputsto is a data integration framework designed to standardize, validate, and route inputs from multiple sources into processing pipelines. It emphasizes modularity and extensibility, allowing developers to add new input adapters and processing steps without modifying core logic.

Its architecture comprises layers for sources and adapters, validation and normalization, transformation, routing, and sinks. Adapters translate source data into a common representation; the validation layer enforces schemas and types; the transformation layer applies enrichment or mapping; the routing layer dispatches events to sinks, which persist or forward the data.

Inputsto supports declarative configuration via schemas or manifests that describe sources, rules, and routing policies. It can be used with message buses, REST endpoints, file uploads, and streaming sources, and attaches provenance metadata to inputs.

History: Inputsto originated as an open-source concept in the early 2020s within a hypothetical software ecosystem and has since inspired several experimental adapters and reference implementations.

Use cases include data ingestion for data lakes, API input validation, IoT device streams, and ETL pipelines. It is designed to help ensure consistency across heterogeneous data sources and to provide traceable, rule-driven processing of inputs.

Limitations include potential overhead from multi-stage processing and the need for well-defined schemas and governance over adapter quality and versioning. As with any framework, effective use depends on clear data contracts and ongoing maintenance of adapters and rules.

Related topics include data pipelines, schema validation, and data provenance.