Frequently Asked Questions

It ranges from a few seconds to several minutes, up to 20 minutes for larger schemas. Time taken increases proportionally with the size of the source and target schemas.

Note that this is only for the initial generation. When using existing pipelines, it is deterministic and thus executes immediately.

Lume currently supports JSON for source data. CSV and XML is in beta. Reach out if you’re interested or have other required formats.

1. Lume infers the schema from the data sample.
2. Lume uses the values of source data to create a more holistic semantic understanding of your source key definition and your source data as a whole. This helps increase mapping accuracy significantly.

Lume recreates the human process of mapping data. In this step, it is common that the source keys are not semantically meaningful. Namely, key names not be related to what the data is actually storing. Thus, it is common to analyze the data to understand what the property truly is storing. Lume goes through this understanding process via its AI.

Target schemas conform to the JSON Schema protocol.