What is schema-on-read?
Schema-on-read is an approach where data is stored in its raw form and structure is applied only when the data is queried, rather than when it is written. It contrasts with schema-on-write, offering flexibility to store varied data now and decide how to interpret it later.
Traditional databases use schema-on-write: you define the structure up front, and data must conform before it can be stored. Schema-on-read flips this, store data raw, and impose a schema at query time, interpreting the structure only when you read it.
- Schema-on-write enforces structure early; reliable but rigid, and slower to onboard new or varied data.
- Schema-on-read stores first and structures later; flexible for diverse, evolving or unstructured data (common in data lakes).
Schema-on-read shines when you don't yet know all the questions you'll ask, or the data's shape varies, but it pushes the interpretation effort onto whoever queries.
iDBQuery reduces that interpretation burden. When you connect a source, it introspects the structure automatically and its semantic layer infers meaning, so even loosely structured or unfamiliar data becomes askable in plain language without you defining a schema by hand first. For files, folders and documents, iDBQuery ingests them and makes their content queryable on read, applying structure as needed to answer your question. Whether your data is rigidly modelled or raw and varied, you get the same experience, ask a question, get a cited answer, with iDBQuery handling the structure interpretation for you.
Updated 2026-06-22