Definition — how data is described
Schema
7 open standards for Schema in a modern data architecture, each with an opinionated judgement: Adopt, Situational, Assess, or Caution.
Start with XML Schema, JSON Schema, SQL DDL, AVRO Schema and Protobuf.
Adopt 5 standards
The standard to reach for in new work. Proven, multi-vendor, clearly the default for its slot.
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XML Schema
— XML Schema Definition (XSD)
The schema language for XML — load-bearing in enterprise integration, finance, healthcare, and government with mature tooling.
W3C
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JSON Schema
Default API-payload validation; behind OpenAPI/AsyncAPI.
JSON Schema community / IETF
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SQL DDL
— SQL Data Definition Language
Universal way to describe a relational schema; portable across engines.
ANSI / ISO/IEC 9075
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AVRO Schema
— Apache Avro Schema
Schema language for Kafka payloads; pairs with Schema Registry.
Apache Software Foundation
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Protobuf
— Protocol Buffers
Strong schema-evolution rules; default for gRPC.
Google (open source, vendor-driven)
Assess 2 standards
Promising but not yet proven for production-default use. Track it and prototype, but don't commit your architecture.
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LinkML
— Linked data Modeling Language
Multi-output schema language; strong in biomedical, niche elsewhere.
LinkML community / Monarch Initiative
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Table Schema
— Frictionless Table Schema
Lightweight Frictionless tabular spec; small ecosystem.
Frictionless Data / Open Knowledge Foundation
More in Definition
Definition covers how data is described.
See Schema in context
These standards are one panel of the interactive Data Landscape, which maps every open standard a modern data architecture is built on. The underlying data is a single JSON file; disagree with a judgement? Open an issue.