Apicurio Registry vs Dataphos Schema Registry

Apicurio Registry is an open-source runtime server for storing API designs and schemas as artifacts. Users can add, update, and remove artifacts through a remote REST API. For API discovery, teams can register designs such as OpenAPI, AsyncAPI, and GraphQL so consumers can search and browse APIs, see details, and read generated documentation. For messaging and event streaming, it provides a central place to track schemas and manage data-format evolution. Supported artifact types include OpenAPI, AsyncAPI, GraphQL, Apache Avro, Protocol Buffers, JSON Schema, Kafka Connect schema, WSDL, XML Schema, and ODCS v3.1. Configurable rules can check validity, compatibility, and integrity as artifacts change. Listed storage backends include Apache Kafka, PostgreSQL, and Microsoft SQL Server. Management options include a web console, REST API, command line, Maven plug-in, and Java client. Kafka serializers and deserializers can enforce schemas in producer and consumer applications. The documentation covers self-hosted deployment, including Kubernetes. The quick-start in-memory server is non-persistent and is not intended for production.

Dataphos Schema Registry is an open-source API and self-hosted service for managing schemas in streaming data systems and validating events in flight. It keeps versioned schema history and exposes a REST API for registering, updating, retrieving, and deleting schemas, plus validity and compatibility checks. Validators support JSON, Avro, Protocol Buffers, XML, and CSV. They work with GCP Pub/Sub, Azure Service Bus, Azure Event Hubs, Apache Kafka, Apache Pulsar, and NATS JetStream, and can support producers and consumers using different protocols. Validation sends passing messages to a valid topic and failures to a dead-letter topic. Compatibility modes include backward, forward, and full variants, with transitive options and NONE; BACKWARD is the default. Validity defaults to FULL, with FULL, NONE, and SYNTAX_ONLY documented. The registry and validators run as Kubernetes deployments, using Shell, Helm, or Pulumi options. The Shell quickstart calls for at least 8 GB of available RAM on cluster nodes. Prometheus is optional for metrics and log monitoring.