indexdat

Indexdat is a conceptual data indexing format designed to store and exchange index structures used by search, analytics, and data integrity workflows. The term is generic and not tied to a single project; it describes its logical organization rather than a specific implementation.

Data model: A typical indexdat file begins with a header specifying a version, schema, and optional metadata. The core content comprises index entries mapping keys (such as terms or identifiers) to postings structures that contain pointers to documents, positions, or shards. Entries may include statistics such as document frequency, term frequency, and field-specific payloads.

Serialization and efficiency: Indexdat supports multiple encodings, including binary, JSON, and compressed forms. To optimize space and speed, common techniques include delta-encoding for IDs, run-length encoding for gaps, and optional compression (e.g., deflate, Snappy). It is designed for streaming updates and append-only workflows, with mechanisms for incremental commits.

Applications and workflows: Used to power inverted indexes in lightweight search engines, log analytics, and data warehouses. Producers write indexdat files or streams, while consumers load and merge indices, perform queries, or rebuild statistics. Access patterns emphasize fast lookups by key and efficient range scans.

History and status: There is no single official standard for indexdat. It is described here as a generic concept to illustrate a structured approach to storing index data. Real-world projects may implement similar formats under different names. Adoption depends on interoperability, tooling, and ecosystem support.