dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
- dbt-viewpoint
- slack
- pypa
- data-modeling
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dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Building event-driven applications the easy way in Go.
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Privacy and Security focused Segment-alternative, in Golang and React
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Open-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.
Distributed Stream Processing
tools for working with streams of data
Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.
Amazon Redshift Database Loader implemented in AWS Lambda
Amazon Kinesis Aggregators provides a simple way to create real time aggregations of data on Amazon Kinesis.
Stateful actors on Apache Flink 2.x and Java 21 — durable per-key state, exactly-once messaging, Kafka and Kinesis I/O, Kubernetes-native deployment. Continues the Apache Stateful Functions programming model on the modern Flink line.