Data Quality for ksqlDB

Data Quality for Streaming Data

Without proactive Data Quality monitoring, data issues can cascade quickly in event-driven streaming platforms like Kafka. For example, if incorrect data and invalid schemas go undetected, downstream applications and services in that ecosystem can fail or run at suboptimal performance.

Since Kafka has a partitioned log model architecture to support vast amounts of streaming data, it lacks the structured tables and schemas found in relational databases. This architectural difference means traditional Data Quality checks deployed in databases won’t work in Kafka.

That’s where the Lightup connector for ksqlDB comes in, offering a way to read streaming data from all “Topics” stored in Kafka clusters by:

Treating a Kafka cluster as a data source.
Converting ksqlDB “Topics” to tables in Lightup.
Creating a “Default” schema automatically for Kafka.

Lightup Connector for ksqlDB

The Lightup connector for ksqlDB enables proactive Data Quality monitoring for metadata Auto Metrics for Tables, Schemas, and Columns in Kafka “Topics” (handled as Tables in Lightup).

Technical Requirements

ksqlDB must be installed and configured for stream processing on Kafka clusters.
A Kafka schema registry is necessary to get the schema of the values in each Topic.

Key Benefits

Maintain Optimal Performance

Ensure reliable data in streaming environments to optimize system performance and reduce downtime.

Monitor Streaming Data

Lightup converts Kafka Topics to tables and automatically generates schemas, enabling Data Quality checks on streaming data.

Prevent Downstream Outages

Proactively detect and resolve Data Quality incidents before downstream systems and workloads are impacted.

Resources

Blog

Data Quality and Observability for Streaming Data: Introducing Lightup's New ksqlDB Connector

Docs

ksqlDB (Beta)

Get Started with Lightup Data Quality for ksqlDB

Monitor Data Quality for streaming data in Kafka with Lightup’s ksqlDB connector.

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