Avro

•    Java

Avro is a data serialization system. It is a subproject of Apache Hadoop.

Luigi - Python module that helps you build complex pipelines of batch jobs

•    Python

The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else.

Scalding - A Scala API for Cascading

•    Scala

Scalding is a Scala library that makes it easy to specify Hadoop MapReduce jobs. Scalding is built on top of Cascading, a Java library that abstracts away low-level Hadoop details. Scalding is comparable to Pig, but offers tight integration with Scala, bringing advantages of Scala to your MapReduce jobs.

XLearning - AI on Hadoop

•    Java

XLearning is a convenient and efficient scheduling platform combined with the big data and artificial intelligence, support for a variety of machine learning, deep learning frameworks. XLearning is running on the Hadoop Yarn and has integrated deep learning frameworks such as TensorFlow, MXNet, Caffe, Theano, PyTorch, Keras, XGBoost. XLearning has the satisfactory scalability and compatibility.Besides the distributed mode of TensorFlow and MXNet frameworks, XLearning supports the standalone mode of all deep learning frameworks such as Caffe, Theano, PyTorch. Moreover, XLearning allows the custom versions and multi-version of frameworks flexibly.

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines

•    Python

IPython Notebook(s) demonstrating deep learning functionality.IPython Notebook(s) demonstrating scikit-learn functionality.

BigDL - BigDL: Distributed Deep Learning Library for Apache Spark

•    Scala

A distributed deep learning library for Apache Spark.

nagios-plugins - Hadoop, Docker, Kafka, Elasticsearch, RabbitMQ, Redis, HBase, Solr, Cassandra, ZooKeeper, HDFS, Yarn, Hive, Presto, Drill, Impala, Consul, Spark, Ambari, Hortonworks, Cloudera, MapR, Neo4j, Jenkins, Travis CI, Git, MySQL, Linux, DNS, Whois, SSL Certs, Yum Security Updates, Mesos, Riak, MongoDB, Memcached, Couchbase, CouchDB

•    Perl

Specialised plugins for Hadoop, Big Data & NoSQL technologies, written by a former Clouderan (Cloudera was the first Hadoop Big Data vendor) and modern Hortonworks partner/consultant. Supports a a wide variety of compatible Enterprise Monitoring systems.

Gaffer - A large-scale entity and relation database supporting aggregation of properties

•    Java

Gaffer is a graph database framework. It allows the storage of very large graphs containing rich properties on the nodes and edges. Several storage options are available, including Accumulo, Hbase and Parquet. It is designed to be as flexible, scalable and extensible as possible, allowing for rapid prototyping and transition to production systems.

presto - Distributed SQL query engine for big data

•    Java

Presto

deeplearning4j - Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark

•    Java

Deeplearning4j Monorepo

Alluxio - Data orchestration for analytics and machine learning in the cloud

•    Java

Alluxio (formerly known as Tachyon) is a virtual distributed storage system. It bridges the gap between computation frameworks and storage systems, enabling computation applications to connect to numerous storage systems through a common interface.

Apache Trafodion - Webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop.

•    C++

Apache Trafodion is a webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. Trafodion builds on the scalability, elasticity, and flexibility of Hadoop. Trafodion extends Hadoop to provide guaranteed transactional integrity, enabling new kinds of big data applications to run on Hadoop.

Apache Tez - A Framework for YARN-based, Data Processing Applications In Hadoop

•    Java

Apache Tez is an extensible framework for building high performance batch and interactive data processing applications, coordinated by YARN in Apache Hadoop. Tez improves the MapReduce paradigm by dramatically improving its speed, while maintaining MapReduce’s ability to scale to petabytes of data. Important Hadoop ecosystem projects like Apache Hive and Apache Pig use Apache Tez, as do a growing number of third party data access applications developed for the broader Hadoop ecosystem.

Cascalog - Data processing on Hadoop

•    Clojure

Cascalog is a fully-featured data processing and querying library for Clojure or Java. The main use cases for Cascalog are processing "Big Data" on top of Hadoop or doing analysis on your local computer. Cascalog is a replacement for tools like Pig, Hive, and Cascading and operates at a significantly higher level of abstraction than those tools.

dist-keras - Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark

•    Python

Distributed Deep Learning with Apache Spark and Keras. Distributed Keras is a distributed deep learning framework built op top of Apache Spark and Keras, with a focus on "state-of-the-art" distributed optimization algorithms. We designed the framework in such a way that a new distributed optimizer could be implemented with ease, thus enabling a person to focus on research. Several distributed methods are supported, such as, but not restricted to, the training of ensembles and models using data parallel methods.

moosefs - MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System

•    C

MooseFS is a Petabyte Open Source Network Distributed File System. It is easy to deploy and maintain, fault tolerant, highly performing, easily scalable, POSIX compliant. MooseFS Linux Client uses FUSE. MooseFS macOS Client uses FUSE for macOS.

incubator-hudi - Upserts And Incremental Processing on Big Data

•    Java

Hoodie is a Apache Spark library that provides the ability to efficiently do incremental processing on datasets in HDFS

Cascading - Data Processing Workflows on Hadoop

•    Java

Cascading is a Data Processing API, Process Planner, and Process Scheduler used for defining and executing complex, scale-free, and fault tolerant data processing workflows on an Apache Hadoop cluster. It is a thin Java library and API that sits on top of Hadoop's MapReduce layer and is executed from the command line like any other Hadoop application.

LizardFS - Software Defined Storage, Distributed, Parallel, Scalable, Fault-tolerant, Geo-Redundant and Highly available file system

•    C++

LizardFS Software Defined Storage is a distributed, parallel, scalable, fault-tolerant, Geo-Redundant and highly available file system. It spreads data over a number of physical servers, making it visible to an end user as a single file system.

gis-tools-for-hadoop - The GIS Tools for Hadoop are a collection of GIS tools for spatial analysis of big data

The GIS Tools for Hadoop are a collection of GIS tools that leverage the Spatial Framework for Hadoop for spatial analysis of big data. The tools make use of the Geoprocessing Tools for Hadoop toolbox, to provide access to the Hadoop system from the ArcGIS Geoprocessing environment. Start out by navigating to samples and following the instructions provided with each sample.There are also tutorials for using the GP tools and aggregation methods.