Displaying 1 to 20 from 24 results

Vespa - Yahoo's big data serving engine

Vespa is an engine for low-latency computation over large data sets. It stores and indexes your data such that queries, selection and processing over the data can be performed at serving time. Vespa is serving platform for Yahoo.com, Yahoo News, Yahoo Sports, Yahoo Finance, Yahoo Gemini, Flickr.

genie - Distributed Big Data Orchestration Service

Genie is a federated job orchestration engine developed by Netflix. Genie provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, Spark, Presto, Sqoop and more. It also provides APIs for managing the metadata of many distributed processing clusters and the commands and applications which run on them.See the official website to find documentation about Genie and specific documentation for various releases.

DataflowJavaSDK - Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines

Google Cloud Dataflow SDK for Java is a distribution of Apache Beam designed to simplify usage of Apache Beam on Google Cloud Dataflow service. This artifact includes the parent POM for other Dataflow SDK artifacts.

Spark - Fast Cluster Computing

Apache Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write. To run programs faster, Spark offers a general execution model that can optimize arbitrary operator graphs, and supports in-memory computing, which lets it query data faster than disk-based engines like Hadoop.

Presto - Distributed SQL query engine for big data

Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. It allows querying data from relational / nosql databases. A single Presto query can combine data from multiple sources, allowing for analytics across your entire organization. It is developed by Facebook.

Apache Metron - Real-time Big Data Security

Metron integrates a variety of open source big data technologies in order to offer a centralized tool for security monitoring and analysis. Metron provides capabilities for log aggregation, full packet capture indexing, storage, advanced behavioral analytics and data enrichment, while applying the most current threat intelligence information to security telemetry within a single platform.

Apache REEF - a stdlib for Big Data

Apache REEF (Retainable Evaluator Execution Framework) is a library for developing portable applications for cluster resource managers such as Apache Hadoop YARN or Apache Mesos. For example, Microsoft Azure Stream Analytics is built on REEF and Hadoop.

Hue - The open source Apache Hadoop UI

Hue is a Web application for interacting with Apache Hadoop. It supports a FileBrowser for accessing HDFS, JobBrowser for accessing MapReduce jobs (MR1/MR2-YARN), Job Designer for creating MapReduce/Streaming/Java jobs, HBase Browser for exploring and modifying HBase tables and data, Oozie App for submitting and scheduling workflows and bundles, A Pig/HBase/Sqoop2 shell, Beeswax application for executing Hive queries, Search app for querying Solr and Solr Cloud.

Cascalog - Data processing on Hadoop

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.

Facets - Visualizations for machine learning datasets

The facets project contains two visualizations for understanding and analyzing machine learning datasets: Facets Overview and Facets Dive. The visualizations are implemented as Polymer web components, backed by Typescript code and can be easily embedded into Jupyter notebooks or webpages.

Calliope - Bridge between Cassandra and Spark framework

Calliope provides a bridge between Cassandra and Spark framework allowing you to create those magical, realtime bigdata apps with ease. It is a library providing an interface to consume data from Cassandra to spark and store RDDs from Spark to Cassandra.

Postgres-XL - Scalable Open Source PostgreSQL-based Database Cluster

Postgres-XL is a horizontally scalable open source SQL database cluster, flexible enough to handle varying database workloads like OLTP, Business Intelligence requiring MPP parallelism, Key value store, GIS Geospatial and lot more.

Fluo - Make incremental updates to large data sets stored in Apache Accumulo

Apache Fluo (incubating) is an open source implementation of Percolator (which populates Google's search index) for Apache Accumulo. Fluo makes it possible to update the results of a large-scale computation, index, or analytic as new data is discovered. When combining new data with existing data, Fluo offers reduced latency when compared to batch processing frameworks (e.g Spark, MapReduce).

Apache Beam - Unified model for defining both batch and streaming data-parallel processing pipelines

Apache Beam is an open source, unified model for defining both batch and streaming data-parallel processing pipelines. Using one of the open source Beam SDKs, you build a program that defines the pipeline. The pipeline is then executed by one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow.

AsterixDB - Big Data Management System (BDMS)

AsterixDB is a BDMS (Big Data Management System) with a rich feature set that sets it apart from other Big Data platforms. Its feature set makes it well-suited to modern needs such as web data warehousing and social data storage and analysis. It is a highly scalable data management system that can store, index, and manage semi-structured data, but it also supports a full-power query language with the expressiveness of SQL (and more).

ConcourseDB - Self-tuning database designed for both transactions and ad hoc analytics across time

ConcourseDB is a distributed self-tuning database with automatic indexing, version control and ACID transactions. ConcourseDB provides a more intuitive approach to data management that is easy to deploy, access and scale while maintaining the strong consistency of traditional database systems.

Shark - Hive on Spark

Shark is an open source distributed SQL query engine for Hadoop data. It brings state-of-the-art performance and advanced analytics to Hive users. It runs Hive queries up to 100x faster in memory, or 10x on disk. it is a large-scale data warehouse system for Spark designed to be compatible with Apache Hive.

StratoSphere - Cloud Computing Framework for Big Data Analytics

The Stratosphere System is an open-source cluster/cloud computing framework for Big Data analytics. It comprises of An extensible higher level language (Meteor) to quickly compose queries for common and recurring use cases, A parallel programming model (PACT, an extension of MapReduce) to run user-defined operations, An efficient massively parallel runtime (Nephele) for fault tolerant execution of acyclic data flows.

Big Data Twitter Demo

This demo analyzes tweets in real-time, even including a dashboard. The tweets are also archived in Azure DB/Blob and Hadoop where Excel can be used for BI!