Schema Registries edit   discuss  

Our list of and information on schema registries, including the Hive Metastore, the Confluent and Hortonworks Schema Registries, and alternatives to these.

Category Definition

Tools that support the definition, management and serving of Data Storage Format schemas for use in the serialisation and de-serialisation of data, primarily with Streaming Data Stores. Will support an API (and often a web user interface) for managing and retrieving schemas, and will often support schema evolution checks (ensuring changes are forward or backward compatible or both), and an SDK that integrates with clients to allow structured data to be read and written directly. May also support serving of the libraries required to perform serialisation/de-serialisation, and high availability configurations.

Open Source Streaming Data Schema Registries

Confluent Schema RegistryCentral definition of schemas for reading and writing from/to Kafka topics, with support for a range of technologies (including the Kafka APIs, Kafka Connect, Kafka Streams, NiFi and StreamSets)
Hortonworks Schema RegistryCentral definition of Avro schemas for use in NiFi, Kafka Producers/Consumers and Streaming Analytics Manager
Avro Schema RegistryCompatible with Confluence Schema Registry API, but re-implemented in Ruby backed by Postgres - https://github.com/salsify/avro-schema-registry
Landoop Schema Registry UIWeb based user interface for the Confluent Schema Registry - https://github.com/Landoop/schema-registry-ui

Streaming Data Schema Registry Alternatives

Schemas can of course be managed and maintained if your configuration management tool, however these will not be available outside of your code base (e.g. to third party tools such as NiFi or StreamSets).

Cloudera have a three part blog post on how to roll your own schema management tool for Kafka using a Kafka topic to store your schemas - part1; part2; part3

Hive Metastore

The Hive Metastore fulfils a similar function for data stored in Hadoop Compatible File Systems and Object Stores, however serves a wider range of table metadata (including how it’s structured on disk), and doesn’t include some features like schema lifecycle management.

This presentation from Hortonworks describes their view of the future of the Hive Metastore, including it’s separation from Hive and integration with the schema registry.

Blog Posts