Best Big Data Processing and Distribution Software

Big data processing and distribution systems offer a way to collect, distribute, store, and manage massive, unstructured data sets in real time. These solutions provide a simple way to process and distribute data amongst parallel computing clusters in an organized fashion. Built for scale, these products are created to run on hundreds or thousands of machines simultaneously, each providing local computation and storage capabilities. Big data processing and distribution systems provide a level of simplicity to the common business problem of data collection at a massive scale and are most often used by companies that need to organize an exorbitant amount of data. Many of these products offer a distribution that runs on top of the open-source big data clustering tool Hadoop.

Companies commonly have a dedicated administrator for managing big data clusters. The role requires in-depth knowledge of database administration, data extraction, and writing host system scripting languages. Administrator responsibilities often include implementation of data storage, performance upkeep, maintenance, security, and pulling the data sets. Businesses often use big data analytics tools to then prepare, manipulate, and model the data collected by these systems.

To qualify for inclusion in the Big Data Processing and Distribution category, a product must:

  • Collect and process big data sets in real-time
  • Distribute data across parallel computing clusters
  • Organize the data in such a manner that it can be managed by system administrators and pulled for analysis
  • Allow businesses to scale machines to the number necessary to store its data

Big Data Processing and Distribution Software Grid® Overview

The best Big Data Processing and Distribution Software products are determined by customer satisfaction (based on user reviews) and market presence (based on products’ scale, focus, and influence) and placed into four categories on the Grid®:
  • Products in the Leader quadrant are rated highly by G2 Crowd users and have substantial Market Presence scores. Leaders include: Hadoop HDFS and Google BigQuery
  • High Performers are highly rated by their users, but have not yet achieved the Market Presence of the Leaders.
  • Contenders have significant Market Presence and resources, but have received below average user Satisfaction ratings or have not yet received a sufficient number of reviews to validate the solution.
  • Niche solutions do not have the Market Presence of the Leaders. They may have been rated positively on customer Satisfaction, but have not yet received enough reviews to validate them. Niche products include: Cloudera and Hortonworks Data Platform
G2 Crowd Grid® for Big Data Processing and Distribution
Leaders
High Performers
Contenders
Niche
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    Big Data Processing and Distribution reviews by real, verified users. Find unbiased ratings on user satisfaction, features, and price based on the most reviews available anywhere.

    Hadoop HDFS is a distributed, scalable, and portable filesystem written in Java.


    BigQuery is Google's fully managed, petabyte scale, low cost enterprise data warehouse for analytics. BigQuery is serverless. There is no infrastructure to manage and you don't need a database administrator, so you can focus on analyzing data to find meaningful insights using familiar SQL. BigQuery is a powerful Big Data analytics platform used by all types of organizations, from startups to Fortune 500 companies.



    Cloudera, based in Palo Alto, California, U.S, offers Cloudera Enterprise, a platform that includes Cloudera Analytic DB (for BI & SQL workloads based on Apache Impala), Cloudera Data Science & Engineering (for data processing and machine learning based on Apache Spark and Cloudera Data Science Workbench), and Cloudera Operational DB (for real-time data serving based on Apache HBase and Apache Kudu). Through their SDX (shared data experience) technologies, the platform provides unified security, governance, and metadata management across these workloads as well as across deployment environments. Cloudera’s platform is available on-premises; across the major cloud environments (including native object store support for S3 and ADLS); and as a managed service under the Cloudera Altus brand.


    Making big data simple


    Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed. And with its serverless approach to resource provisioning and management, you have access to virtually limitless capacity to solve your biggest data processing challenges, while paying only for what you use.


    Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data such as video, audio, application logs, website clickstreams, and IoT telemetry, so you can get timely insights and react quickly to new information.


    Oracle Big Data offers an integrated portfolio of products to help organize and analyze diverse data sources alongside existing data.


    Qubole delivers a Self-Service Platform for Big Data Analytics built on Amazon, Microsoft and Google Clouds


    Amazon EMR is a web-based service that simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective to distribute and process vast amounts of data across dynamically scalable Amazon EC2 instances.


    Apache Spark for Azure HDInsight is an open source processing framework that runs large-scale data analytics applications.


    Azure Data Lake Store is secured, massively scalable, and built to the open HDFS standard, allowing you to run massively-parallel analytics.


    Google Cloud Dataprep is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis. Cloud Dataprep is serverless and works at any scale.


    MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports many mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use, and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified Big Data platform.


    Apache Ambari is a software project designed to enable system administrators to provision, manage and monitor a Hadoop cluster, and also to integrate Hadoop with the existing enterprise infrastructure.


    Apache Apex is an enterprise grade native YARN big data-in-motion platform designed to unify stream processing as well as batch processing.


    Apache Beam is an open source unified programming model designed to define and execute data processing pipelines, including ETL, batch and stream processing.


    Apache Chukwa is an open source data collection system for monitoring large distributed systems.


    Apache Falcon is a feed processing and feed management system designed to make it easier for end consumers to onboard their feed processing and feed management on hadoop clusters.


    HDInsight is a fully-managed cloud Hadoop offering that provides optimized open source analytic clusters for Spark, Hive, MapReduce, HBase, Storm, Kafka, and R Server backed by a 99.9% SLA.


    Azure Time Series Insights is a fully managed analytics, storage, and visualization service for managing IoT-scale time-series data in the cloud. It provides massively scalable time-series data storage and enables you to explore and analyze billions of events streaming in from all over the world in seconds.


    Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Operations that used to take hours or days take seconds or minutes instead, and you pay only for the resources you use (with per-second billing). Cloud Dataproc also easily integrates with other Google Cloud Platform (GCP) services, giving you a powerful and complete platform for data processing, analytics and machine learning.


    HVR is designed to move large volumes of data fast and efficiently in complex environments for real-time updates.


    NewSci Platform is a nonprofit big data solution


    Allows very large Adabas files to be separated into multiple, smaller physical files with no changes to the application. Available for Adabas on mainframe. Read more


    Altiscale Data Cloud is a fully managed Big Data platform, delivering instant access to production-ready Hadoop and Spark.


    AMETRAS Automatic Documents Processing can help you collect relevant information from your documents in order to process, provide and distribute them.


    Apache AsterixDB is a scalable, open source Big Data Management System (BDMS).


    Apache Bahir provides extensions to multiple distributed analytic platforms, extending their reach with a diversity of streaming connectors and SQL data sources.


    Apache Fluo is an open source implementation of Percolator (which populates Google's search index) for Apache Accumulo.


    Bigstep's Bare Metal Cloud is purpose-built for big data. It is designed to enable organizations to instantly create private data centers for big data workloads, by using architectural blueprints tailored to specific use cases.


    BlueData is a Big Data infrastructure software that reduce the complexity, cost, and time to deploy Hadoop and Spark and enable Big-Data-as-a-Service (BDaaS)


    Bright Computing provides comprehensive software solutions for provisioning and managing HPC clusters, Hadoop clusters, and OpenStack private clouds in your data center or in the cloud.


    Collibra is a cross-organizational platform designed to break down the traditional data silos, freeing the data so all users have access.


    Tervela Data Fabric is a lightening-fast, fault-tolerant platform that allows you to capture, share, and distribute data from hundreds of enterprise and cloud data sources down to a diverse set of downstream applications and environments.


    XenonStack is a software company that specializes in product development and providing DevOps, big data integration, real time analytics and data science solutions.


    FICO Decision Management Platform Streaming provides a fully integrated solution for any data -- Big Data or otherwise -- to rapidly generate powerful insights and precise decisioning from the most diverse range of sources. The Platform can import, normalize and synthesize data from any source to quickly analyze the best data to generate decisions, enabling organizations to respond to signals in the data in real-time


    A New Lightweight, Distributed Data Processing Engine


    HCube is a Hortonworks certified and multi-functional data ingestion and analytics solution.


    Combines open source Hadoop and Spark to cost-effectively analyze and manage big data Combines Hadoop and Spark Integrates Hadoop and Spark for fast processing of any type of data at scale. Improves ROI Provides data management and analytical tools to enhance Hadoop capabilities. Helps improve your ROI, whether in the cloud or on-premises. Scalable and adaptible Helps integrate Hadoop as part of a hybrid architecture that supports multiple data types and technologies. Provides the scalability and adaptability you need for big data analytics. Open source support Built on IBM Open Platform, which provides complete open source distribution of Apache ecosystem components. Enhances your ecosystem Provides deployment options and an extended portfolio of capabilities to help you make the most of Hadoop.


    The Infoworks Autonomous Data Engine automates data engineering for end-to-end big data workflow processes from ingestion all the way to consumption, helping customers implement to production in days using 5x fewer people.


    Infoworks addresses the end-to-end challenges you face with end-to-end data engineering solutions that are more than just a pretty user interface. We automate most of the work for you, which is why our Fortune 500 customers are in production in a matter of days.


    Market Locator, powered by Instarea software, allows data rich industries to monetize a highly valuable asset – their big data. A telco can thus create a new revenue stream by providing its anonymized and aggregated big data in the form of a self service location intelligence / population analytics and mobile marketing for their B2B customers. Tested and proven on several markets with world-class telcos such as Slovak Telekom (Deutsche Telekom Group), Orange or O2. Delivered either on a partnership basis or license fee model. Get the most out of your data!


    MPS IntelliVector is a data extraction and process automation solution tailored for the financial, insurance and government sector.


    Paxata is the only enterprise-grade solution built for interactive, self-service data preparation at scale.


    Snowplow, the event analytics platform.


    SureView Analytics is a solution that allows you to integrate structured sources of data with search, query and pattern discovery capabilities, and more.


    The Syncfusion Big Data Platform is the first and the only complete Hadoop distribution designed for Windows. Its users can develop on Windows using familiar tools, and deploy on Windows. Syncfusion has taken the advantages of the Hadoop environment – from easy querying across structured and unstructured data to cost-effective storage of any amount of data using commodity hardware with linear scalability- and made them available on Windows. With extremely minimal prerequisites and no manual configuration, the platform provides an easy-to-use environment for working with popular big data tools such as Pig and Hive. The industry-tested Syncfusion Big Data Platform gives users complete access to the power of the Hadoop environment - and the backing of an experienced team providing the samples and support that will get them up and running quickly.


    Trax Technologies provides cloud-based Big Data solutions for buyers and sellers of logistics services worldwide.


    Upsolver is a Streaming Data Preparation Platform. It removes the complexity from big and streaming data preparation projects and shortens their implementation time from weeks/months to several hours, literally. Powered by a cutting-edge Volcano technology, it queries Amazon S3 in less than a millisecond and stores 10x more data in RAM - allowing you to meet any scale and performance needs without complex data engineering work. Upsolver is packaged as a Public or Private Cloud.


    ViZiX Big Data IoT Platform allows you to seamlessly Collect, Store, Analyze, Report and Act on wireless sensors data streams in real time. ViZix main features include:   • A web-based interface, user configurable at ALL levels   • Support for Big Data Fractal Multi-Tenancy™ to support hierarchical, multi-element Implementations   • Designed for seamless Integration with existing enterprise systems (ERP, SCM, WMS, …)   • Secure (SSL/TLS)   • Complex Event Processing: trigger custom events and/or alerts when complex conditions occur among event streams   • And more...


    With a global data collection engine, artificial intelligence-based analysis, and automated remediation, the ZeroFOX Platform protects you from cyber, brand and physical threats on social media & digital platforms.


    Kate from G2 Crowd

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