Apache Camel is an open source integration framework with 350+ connectors. Write routes in Java, YAML, or XML. Run on Spring Boot, Quarkus, or standalone. Apache License 2.0.
- camel
- integration
- java
- microservices
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Apache Camel is an open source integration framework with 350+ connectors. Write routes in Java, YAML, or XML. Run on Spring Boot, Quarkus, or standalone. Apache License 2.0.
Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
An ultra-lightweight and blazing-fast Messaging Bus/MQTT Broker for Edge & SDV
Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
Apache Spark to Apache Cassandra connector
MongoDB data stream pipeline tools by YouGov (adopted from MongoDB)
EventMesh is a new generation serverless event middleware for building distributed event-driven applications.
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.
Data structure and algorithm library for go, designed to provide functions similar to C++ STL
📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
The MongoDB Spark Connector
The Apache Spark - Apache HBase Connector is a library to support Spark accessing HBase table as external data source or sink.
MySQL to PostgreSQL replica system
Neo4j Connector for Apache Spark, which provides bi-directional read/write access to Neo4j from Spark, using the Spark DataSource APIs
A highly optimized double-ended queue
state machine which runs code
Read and write Neuroglancer datasets programmatically.
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Open-source streaming SQL engine written in Rust using Apache Arrow and DataFusion. Supports continuous queries, temporal stream joins, tumbling/session windows, and CDC/Kafka connectors. Lightweight, embeddable, and sub-microsecond latency
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.