Apache Spark - A unified analytics engine for large-scale data processing
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Apache Spark - A unified analytics engine for large-scale data processing
CMAK is a tool for managing Apache Kafka clusters
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
The leader in Customer Data Infrastructure
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
In-memory message queue with an Amazon SQS-compatible interface. Runs stand-alone or embedded.
REST job server for Apache Spark
Compositional, streaming I/O library for Scala
Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses.
Apache Spark to Apache Cassandra connector
GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs
Livy is an open source REST interface for interacting with Apache Spark from anywhere
Sparkling Water provides H2O functionality inside Spark cluster
Apache Livy is an open source REST interface for interacting with Apache Spark from anywhere.
Essential Spark extensions and helper methods ✨😲
Lightweight real-time big data streaming engine over Apache Pekko
Low-code tool for automating actions on real time data | Stream processing for the users.
The Apache Spark - Apache HBase Connector is a library to support Spark accessing HBase table as external data source or sink.
Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
Akka CQRS/ES framework
Serverless proxy for Spark cluster
Neo4j Connector for Apache Spark, which provides bi-directional read/write access to Neo4j from Spark, using the Spark DataSource APIs
A distributed Spark/Scala implementation of the isolation forest and extended isolation forest algorithms for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.
The LinkedIn Fairness Toolkit (LiFT) is a Scala/Spark library that enables the measurement of fairness in large scale machine learning workflows.