Skip to main content

Ecosystem: Apache Flink

Apache Flink® is the backbone of Ververica Unified Streaming Data Platform. It is the core processing engine of the Ververica ecosystem, serving as the foundation for its streaming and batch data processing capabilities. As the original creators of Apache Flink, Ververica maintains a deep connection to the Flink community, driving its ongoing development. This ensures:

  • Close alignment with the latest Flink features and updates.
  • Contributions that benefit both the open-source project and Ververica’s enterprise offerings.
  • Support for Flink users through training, documentation, and community engagement.

Ververica builds on Flink to provide enhanced features, tooling, and operational capabilities, enabling organizations to develop, deploy, and manage complex data-driven applications at scale.

Apache Flink

Apache Flink is the underlying distributed data processing engine that powers Ververica’s platform and solutions, enabling:

  • Real-time stream processing for low-latency, high-throughput processing of continuous data streams.
  • Batch processing that leverages the same APIs for processing historical datasets.
  • Stateful computations to support event-driven architectures with exactly-once state management.

Ververica Unified Streaming Data Platform extends Apache Flink with enterprise-ready features and tools, making it easier for organizations to operationalize and scale their Flink deployments. The Ververica platform enhances Flink in the following ways:

  • Application Lifecycle Management: Simplifies the deployment, versioning, and scaling of Flink applications.
  • Monitoring and Observability: Provides a user-friendly interface for tracking job metrics, resource utilization, and debugging.
  • High Availability and Fault Tolerance: Streamlines the setup and management of resilient Flink clusters.

By integrating Flink into its ecosystem, Ververica offers a comprehensive platform that simplifies the adoption and scalability of real-time and batch data processing for enterprises.

Key Features​

The key Flink features and capabilities leveraged in the Ververica ecosystem include:

Real-Time Machine Learning and Advanced Analytics​

Apache Flink supports streaming analytics and machine learning, which are integral to Ververica’s ecosystem. Flink’s libraries (e.g., Flink ML) allow users to build and deploy real-time machine learning models as part of the streaming data pipelines.

Integration with Other Technologies​

Flink’s versatility allows it to seamlessly integrate with various tools and frameworks within the Ververica ecosystem:

  • Sources and Sinks: Integrates with Kafka, Pulsar, Kinesis, and databases.
  • Storage: Works with cloud-native storage solutions like S3, HDFS, and GCS.
  • Orchestration: Operates efficiently in Kubernetes environments.
  • Metrics: Supports integrations with monitoring systems like Prometheus and Grafana.

Try out Flink

For more information about Apache Flink pre-configured tools and formats:

See also: Apache Paimon, Streamhouse, and Flink CDC.

On this page