# Level up your Kafka applications with the power of schemas

Apache Kafka has become the go-to standard for streaming data and event stores. Let’s explore how schemas and schema management can add value to your event-driven applications on the fully managed Kafka service, IBM Event Streams on IBM Cloud.

**Summary:**
Schemas play a pivotal role in defining the structure of data in Apache Kafka. They serve as a contract between producing and consuming applications, ensuring the compatibility and consistency of data. Additionally, a schema registry supports the Kafka cluster by managing and validating these schemas, while also enabling evolution and versioning. Leveraging these features optimizes the Kafka environment and supports the interoperability of different components within distributed systems.

## What is a Schema?

A schema defines the structure of data. For instance, in the context of a simple Java class modeling an order from an online store, the schema would outline the fields and their types.

## Why Should You Use a Schema?

Kafka transfers data without the validation of message information, which means it lacks visibility into the data being sent and received. By using a schema, applications can work at their own pace while ensuring that the data they exchange is structured and interpretable.

## What is a Schema Registry?

A schema registry serves as a repository for managing and validating schemas within a Kafka cluster, facilitating the management, retrieval, and validation of schemas.

## Optimize Your Kafka Environment by Using a Schema Registry

Utilizing a schema registry ensures consistent data formatting, prevents common errors in application development, and supports strategic goals by treating data as a valuable product. It also facilitates schema evolution, versioning, and data consistency.

## FAQ
### What are the different patterns for schema evolution?
– **Forward Compatibility:** allows producing applications to be updated to a new schema version while all consuming applications continue to consume messages, awaiting migration to the new version.
– **Backward Compatibility:** permits consuming applications to be migrated to a new schema version first, enabling them to consume messages produced in the old format while producing applications are migrated.
– **Full Compatibility:** ensures that schemas are both forward and backward compatible.

### How does a schema registry simplify adherence to data governance policies?
By providing a repository of schema versions used within a Kafka cluster, a schema registry enables convenient tracking and auditing of changes to topic data formats, thereby streamlining adherence to data governance and quality policies.

## What’s Next?

In conclusion, a schema registry is pivotal for managing schema evolution, versioning, and data consistency in distributed systems, supporting interoperability between different components. IBM Event Streams on IBM Cloud provides a Schema Registry as part of its Enterprise plan, optimizing the fully managed Kafka offering.

– **Provision an instance of Event Streams on IBM Cloud [here.](https://cloud.ibm.com/eventstreams-provisioning/6a7f4e38-f218-48ef-9dd2-df408747568e/create)**
– **Learn how to use the Event Streams Schema Registry [here.](https://cloud.ibm.com/docs/EventStreams?topic=EventStreams-ES_schema_registry)**
– **Explore more about Kafka and its use cases.**
– **For setup challenges, refer to the [Getting Started Guide](https://cloud.ibm.com/docs/EventStreams?topic=EventStreams-getting-started) and [FAQs.](https://cloud.ibm.com/docs/EventStreams?topic=EventStreams-faqs)**