Real-time stream processing powered by Apache Flink® and Debezium

Decodable is a cloud-native stream processing platform, powered by Apache Flink and Debezium. With Decodable, you can connect to data sources, process data, and send it to where it needs to go. There’s nothing to deploy or maintain.

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How Decodable Works

Use Decodable’s pre-built connectors to connect to your source and destination systems. Source connections produce to a stream, while sink connections consume from a stream. You control the resources a connection gets by specifying the task size and count.

Streams transport data between any number of Decodable connections and pipelines. Each stream is a publish/subscribe topic with metadata including schema, format, retention, and semantic information about the data (e.g. append-only or CDC).

You can process data in streams in either SQL or code with a pipeline. Just like connections, you specify the resources a pipeline gets by selecting a task size and count. Decodable will scale up to the number you specify.

What can I do with Decodable?

Replicate data from operational databases to your data warehouse in real-time using Debezium-powered change data capture connectors. Low-overhead, high-throughput, continuous data means the analytics and modeling on the freshest data available.

Capture clickstream, orders, inventory updates, product telemetry, and other application events from streaming systems like Apache Kafka. Cleanse and transform event data and ingest it into your data lakes so it's optimized and ready for analytics. Handle everything from data quality to format conversion and partitioning in real-time.

Support multiple use cases without collecting and processing high volume, sensitive data multiple times by running multiple pipelines on the same stream. Pipelines execute in parallel, and can even be written in different languages, making it easy to share data and processing across teams.

Pipelines can be arranged in a directed acyclic graph (DAG) just as you wound in batch data processing. Separate complex jobs into easy to manage units without losing efficiency. Allow downstream teams and processes to further refine data the way they need to without impacting upstream workloads.

A Complete Platform

Powerful Stream Processing

Industry-standard, open source, real-time data processing at scale.

Build jobs in SQL - filter, join, group by and aggregate, use common table expressions (CTEs), match recognize, and more.
Build jobs in code - Use the Apache Flink APIs to build sophisticated real-time data pipelines and apps.