Comparing Kafka Schema Registries

Comparing Kafka Schema Registries

A comprehensive comparison of schema registry solutions for Apache Kafka, and why enterprises are choosing a new approach

Introduction

As organizations scale their Apache Kafka deployments, schema management becomes critical. Schema registries ensure that producers and consumers agree on data formats, preventing data corruption and enabling safe schema evolution. But not all schema registries are created equal.

In this post, we'll compare the leading schema registry solutions—Confluent Schema Registry, Karapace, Apicurio, and our own AxonOps Schema Registry—to help you choose the right solution for your needs.

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The Schema Registry Landscape

Confluent Schema Registry

Confluent Schema Registry is the original and most widely deployed solution. It's tightly integrated with the Kafka ecosystem and offers excellent compatibility guarantees.

Pros:

• Battle-tested in production
• Excellent documentation
• Strong community support

Cons:

• Requires Kafka for storage (coordination overhead)
• Enterprise features require commercial license
• Heavy resource footprint (~500MB+ RAM)
• Limited authentication options in OSS version

Karapace

Developed by Aiven, Karapace is a Python-based drop-in replacement for Confluent Schema Registry.

Pros:

• Apache 2.0 license
• Confluent API compatible
• Lightweight compared to Java

Cons:

• Still requires Kafka for storage
• No built-in authentication or RBAC
• Python runtime dependencies
• Limited enterprise features

Apicurio Registry

Red Hat's Apicurio is a general-purpose schema/API registry with Kafka schema registry compatibility.

Pros:

• Multiple storage backends
• Supports more than Kafka use cases
• OIDC/Keycloak integration

Cons:

• More complex deployment
• JVM-based (~300MB RAM)
• Kafka storage still requires Kafka running
• Broader scope may be overkill for Kafka-only use

Introducing AxonOps Schema Registry

We built AxonOps Schema Registry to address the gaps we saw in existing solutions. Our design principles were:

1. No Kafka Dependency — Use proven databases for storage
2. Enterprise Security Built-in — Not as a paid add-on
3. Lightweight & Fast — Single binary, ~50MB RAM
4. True Multi-DC Support — Active-active without complex setup
5. Full Confluent Compatibility — Drop-in replacement

Feature Comparison

Authentication Comparison

Security Features Comparison

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AxonOps Schema Registry Architecture

Why No Kafka Dependency?

One of our key design decisions was eliminating the Kafka dependency. Here's why:

The Problem with Kafka-Based Storage

1. Circular Dependency: You need the schema registry to serialize messages, but the schema registry needs Kafka to store schemas. This creates bootstrap complexity.
2. Resource Overhead: Running Kafka just for schema storage means maintaining ZooKeeper/KRaft clusters, even if you only need a simple key-value store.
3. Operational Complexity: Kafka storage requires understanding topics, partitions, replication—all for what is essentially a metadata store.
4. Multi-DC Challenges: Cross-datacenter Kafka replication (MirrorMaker, Cluster Linking) adds significant complexity.

The AxonOps Approach

We use proven databases that your operations team already knows:

• PostgreSQL/MySQL: Perfect for single-DC or active-passive setups
• Cassandra: Native multi-DC replication for active-active deployments
• Memory: Zero-config for development and testing

Enterprise Security: Built-in, Not Bolt-on

Security shouldn't require an enterprise license. AxonOps Schema Registry includes:

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Authentication Methods

API Keys with Expiration

auth:
 api_keys:
   enabled: true
   server_secret: "${HMAC_SECRET}"  # Optional HMAC pepper for defense-in-depth

API keys are stored using SHA-256 hashing with optional HMAC-SHA256 for additional security. Keys can have expiration dates and can be revoked instantly.

LDAP/Active Directory

auth:
 ldap:
   enabled: true
   url: "ldaps://ldap.example.com:636"
   base_dn: "dc=example,dc=com"
   user_search_filter: "(uid={0})"
   group_search_filter: "(member={0})"
   group_role_mapping:
     "cn=kafka-admins,ou=groups,dc=example,dc=com": "admin"
     "cn=developers,ou=groups,dc=example,dc=com": "developer"


OIDC (Keycloak, Okta, Auth0)

auth:
 oidc:
   enabled: true
   issuer_url: "https://keycloak.example.com/realms/kafka"
   client_id: "schema-registry"
   audience: "schema-registry"
   role_claim: "groups"
   role_mapping:
     "/schema-registry-admins": "admin"
     "/developers": "developer"


Role-Based Access Control

Four built-in roles with granular permissions:

Additional Security Features

• Rate Limiting: Token bucket algorithm prevents abuse
• Audit Logging: JSON audit trail for compliance
• TLS Certificate Auto-Reload: Update certs without restart
• HashiCorp Vault Integration: Centralized secrets management

Multi-Datacenter: Active-Active Made Simple

For organizations with global deployments, multi-DC support is essential. Here's how the options compare:

AxonOps Multi-DC Architecture

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With Cassandra as the backend:

1. Zero Coordination Overhead: Each registry instance is stateless
2. LOCAL_QUORUM Writes: Strong consistency within each DC
3. Automatic Cross-DC Replication: Cassandra handles it natively
4. Datacenter Failure Tolerance: Other DCs continue operating

storage:
 type: cassandra
 cassandra:
   hosts:
     - "cass-dc1-1.example.com"
     - "cass-dc1-2.example.com"
   keyspace: "schema_registry"
   consistency: "LOCAL_QUORUM"
   local_dc: "dc1"


Performance & Resource Efficiency

Memory Footprint Comparison

AxonOps Schema Registry:     ~50MB
Karapace:                   ~200MB
Apicurio:                   ~300MB
Confluent Schema Registry:  ~500MB+


Why So Lightweight?

1. Go vs JVM: Native binary with minimal runtime
2. No Kafka Client: No embedded consumers/producers
3. Efficient Caching: LRU cache with configurable TTL
4. Connection Pooling: Optimized database connections

Performance Optimizations

• Schema Deduplication: Same content = same ID (SHA-256 fingerprints)
• Canonical Forms: Normalized schemas for efficient comparison
• In-Memory Caching: Sub-millisecond lookups for hot schemas
• Connection Pooling: Configurable pool sizes and lifetimes

Migration: Seamless Transition from Confluent

Moving from Confluent Schema Registry? We've got you covered.

Schema Import API

AxonOps provides a dedicated import API that preserves schema IDs—critical because Kafka messages contain schema IDs in their wire format.

# Export from Confluent
./migrate-from-confluent.sh \
   --source http://confluent-sr:8081 \
   --target http://axonops-sr:8081 \
   --verify


The import API:

• Preserves original schema IDs
• Maintains subject-version mappings
• Ensures new schemas get IDs after imported ones
• Supports incremental migration

Migration Script

We provide a ready-to-use migration script:

./scripts/migrate-from-confluent.sh \
   --source http://confluent-sr:8081 \
   --source-user admin \
   --source-pass secret \
   --target http://axonops-sr:8081 \
   --target-apikey $API_KEY \
   --verify


Integration with AxonOps Platform

AxonOps Schema Registry is fully integrated with the AxonOps platform, providing:

• Unified Dashboard: Monitor schemas alongside Kafka clusters
• Alerting: Get notified on compatibility violations
• Capacity Planning: Track schema growth and storage usage
• Team Management: Centralized user and access control

Deployment Options

Binary Distribution

Download and run—no JVM, no Python, no containers required:

# Download binary directly
curl -LO https://github.com/axonops/axonops-schema-registry/releases/latest/download/schema-registry-linux-amd64
./schema-registry-linux-amd64 -config config.yaml


RPM (RHEL, CentOS, Fedora)

# Add AxonOps yum repository
sudo tee /etc/yum.repos.d/axonops.repo <<EOF
[axonops]
name=AxonOps Repository
baseurl=https://packages.axonops.com/yum/stable
enabled=1
gpgcheck=1
gpgkey=https://packages.axonops.com/gpg.key
EOF

# Install
sudo yum install axonops-schema-registry


DEB (Ubuntu, Debian)

# Add AxonOps apt repository
curl -fsSL https://packages.axonops.com/gpg.key | sudo gpg --dearmor -o /usr/share/keyrings/axonops.gpg
echo "deb [signed-by=/usr/share/keyrings/axonops.gpg] https://packages.axonops.com/apt stable main" | sudo tee /etc/apt/sources.list.d/axonops.list

# Install
sudo apt update && sudo apt install axonops-schema-registry


Docker

docker run -d \
 -p 8081:8081 \
 -v $(pwd)/config.yaml:/etc/schema-registry/config.yaml \
 axonops/schema-registry:latest


Kubernetes (Helm)

helm repo add axonops https://charts.axonops.com
helm install schema-registry axonops/schema-registry \
 --set storage.type=postgresql \
 --set storage.postgresql.host=postgres.default.svc


Licensing & Support

Open Source (Apache 2.0)

AxonOps Schema Registry is fully open source under the Apache 2.0 license. You get:

• All features included (no "enterprise tier")
• Freedom to modify and distribute
• Community support via GitHub

Commercial Support

For organizations requiring production support, AxonOps offers:

• 24/7 Support: Direct access to engineering team
• SLA Guarantees: Response time commitments
• Professional Services: Migration assistance, architecture review
• Training: Team enablement and best practices

Contact [email protected] for enterprise support options.

Getting Started

Quick Start (Memory Backend)

# config.yaml
server:
 host: "0.0.0.0"
 port: 8081

storage:
 type: memory

compatibility:
 default_level: BACKWARD
./schema-registry -config config.yaml


Production Setup (PostgreSQL)

# config.yaml
server:
 host: "0.0.0.0"
 port: 8081

storage:
 type: postgres
 postgres:
   host: "postgres.example.com"
   port: 5432
   username: "${DB_USER}"
   password: "${DB_PASS}"
   database: "schema_registry"
   ssl_mode: "require"

auth:
 basic:
   enabled: true
   bootstrap_user: "admin"
   bootstrap_password: "${ADMIN_PASS}"
 rbac:
   enabled: true
   default_role: "readonly"

security:
 tls:
   enabled: true
   cert_file: "/etc/ssl/server.crt"
   key_file: "/etc/ssl/server.key"

compatibility:
 default_level: BACKWARD


Conclusion

Choosing a schema registry is a long-term decision. Here's our recommendation:

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AxonOps Schema Registry represents a new generation of schema management—built for modern cloud-native deployments, with enterprise security included from day one, and without the operational overhead of Kafka-based storage.

Ready to try it? Check out our GitHub repository or contact us for a demo.

Resources

• GitHub: github.com/axonops/axonops-schema-registry
• Documentation: axonops.com/docs/schema-registry
• Migration Guide: axonops.com/docs/schema-registry/migration
• Support: [email protected]

AxonOps Schema Registry is developed by AxonOps Limited. Apache Kafka is a trademark of the Apache Software Foundation. Confluent is a trademark of Confluent, Inc.

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