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Tag: Data pipelines and messaging
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The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.

  • metadata
  • datadiscovery
  • dataquality
  • data-profiling

Instant messaging platform. Backend in Go. Clients: Swift iOS, Java Android, JS webapp, scriptable command line; chatbots

  • chat
  • chat-application
  • chatapp
  • go

Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.

Glow is an easy-to-use distributed computation system written in Go, similar to Hadoop Map Reduce, Spark, Flink, Storm, etc. I am also working on another similar pure Go system, https://github.com/chrislusf/gleam , which is more flexible and more performant.

Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses.

The fully compliant, embeddable high-performance Go MQTT v5 server for IoT, smarthome, and pubsub

  • mqtt
  • mqtt-broker
  • mqtt-server
  • mqtt-smarthome

MongooseIM is Erlang Solutions' robust, scalable and efficient XMPP server, aimed at large installations. Specifically designed for enterprise purposes, it is fault-tolerant and can utilise the resources of multiple clustered machines.

  • mongooseim
  • erlang
  • xmpp
  • jabber

A platform that makes it easy for developers to build realtime, cost-effective, operations-focused applications

Performant pure-PHP AMQP (RabbitMQ) sync/async (ReactPHP) library

  • amqp
  • amqp-client
  • amqp0-9-1
  • php

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

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.