Documentinto

Documentinto is a term used in data processing to describe a software component or function that converts input data into document-oriented representations suitable for document stores and document-centric workflows. It serves as a bridge between structured data sources and document databases, enabling the serialization and organization of data as documents with nested structures.

Core capabilities of documentinto include handling multiple input formats such as JSON, CSV, XML, YAML, and relational query results, and producing outputs as individual documents, batches, or streaming document streams. It emphasizes preserving hierarchical relationships, supporting nested objects, arrays, and document references. Typical features include field mapping, type inference, data validation, deduplication, error reporting, and optional metadata attachment. Some implementations offer schema-on-read approaches and configurable serialization options to target formats like JSON documents, BSON, or XML.

In practice, documentinto is used within ETL pipelines, data migration projects, content management systems, and data ingestion workflows for document databases such as MongoDB, Couchbase, or specialized search indexes. It often provides a pipeline or API that accepts a source, a destination, and a set of transformation or mapping rules, allowing users to tailor how source fields map to document fields, how nested structures are created, and how identifiers are generated.

Example usage (conceptual): documentinto("path/to/users.csv", { target: "users", mapping: { id: "user_id", name: "full_name" }, outputFormat: "JSON" }). While not tied to a formal standard, documentinto concepts appear in various data integration tools and libraries as a means to generate document-ready representations from heterogeneous data sources.

See also: document databases, data ingestion, ETL, data serialization, JSON, BSON.