Process data between Kafka topics to curate data for other teams. Transform formats, route, cleanse, mask, filter, and aggregate data for different services.
Directly connect streaming data into Snowflake - lowering data latency and reducing ingestion costs. The Decodable connector is pre-integrated with the Snowflake Snowpipe Streaming API to make connections quick and simple.
Unify batch and streaming pipeline management. The open source dbt-Decodable adapter makes it possible to manage streaming and batch transformation in a single workflow through the dbt interface.
Connect Confluent Cloud and Confluent Platform to applications and services without replatforming. Enable ML/AI engineers, frontend developers, and data engineers to easily work with operational streaming data.
Format and denormalize complex event data for applications that are already powered by operational databases such as Cassandra, MongoDB, Redis and more. Build real-time analytics and product features directly into applications.
Connect, build and manage SQL pipelines that transform and enrich incoming real-time data from any source. Ingest streaming event data into Apache Pinot real-time tables enabling always-up-to-date customer-facing analytics, at any scale.
Easily create fast, high volume streams, without data loss, and build a unified source of truth. Parse, transform, enrich and filter source topics to drive user behavior, fraud detection, AI feature store, and other real-time scenarios.