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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
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Compare Big Data Processing and Distribution Software
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    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.

    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.

    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.

    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.

    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.

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

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

    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.

    Qubole is revolutionizing the way companies activate their data--the process of putting data into active use across their organizations. With Qubole's cloud-native Data Platform for analytics and machine learning, companies exponentially activate petabytes of data faster, for everyone and any use case, while continuously lowering costs. Qubole overcomes the challenges of expanding users, use cases, and variety and volume of data while constrained by limited budgets and a global shortage of big data skills. Qubole's intelligent automation and self-service supercharge productivity, while workload-aware auto-scaling and real-time spot buying drive down compute costs dramatically. Qubole offers the only platform that delivers freedom of choice, eliminating legacy lock in--use any engine, any tool, and any cloud to match your company's needs.

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

    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.

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

    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.

    ASG Technologies’ Enterprise Data Intelligence Solution delivers a tool-agnostic solution that supports the creation of custom metadata interfaces for your enterprise sources, providing a complete data lineage knowledge base. The range and flexibility offered by ASG includes discovery of mainframe, distributed and other ETL code, analyzing to ensure there are no gaps in your end-to-end lineage.

    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.

    Snowplow is an enterprise-grade data collection platform for companies who want the freedom and flexibility of owning their data pipeline, but not the hassle and cost of maintaining it. The Snowplow tech is built from the ground up to maximize data granularity, richness and scalability; our customers use our tech stack to track 100s of millions of events each day. Snowplow is the best way to collect event level data with a focus on: * Data richness * Data quality * Highly structured data * Flexible data pipeline that evolves with your business * Real-time data * Collect data across all of your own systems and third party applications

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

    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 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.

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

    Apache Storm is a distributed, fault-tolerant, open-source, real-time event processing solution for large, fast streams of data.

    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.

    A New Lightweight, Distributed Data Processing Engine

    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.

    All the talk about qualitative data analysis is for naught if you can’t understand language as it is spoken. That is what Natural Language Processing (NLP) is all about. NewSci NLP brings this power to organization’s seeking to extract insights from their unstructured data. Just as you know what a person is saying when you hear, “I’m hungry, I want an apple” vs. “I really want an Apple™ instead of a PC,” so now can a computer. NewSci NLP enables a computer to understand the people, places, and things important to your organization. This, in turn, allows your unstructured data to be analyzed just like your structured data. With NewSci NLP your organization will enjoy qualitative analysis (the Why behind the numbers) alongside your quantitative analytics. Uses models customized to your organization; the domain in which you operate; the quality of your recordings; and even local and regional dialects to deliver the highest level of transcription accuracy. Captures your organization’s domain and unique characteristics to enable deep Natural Language Understanding analysis and Natural Language Generation. Your NewSci Ontology will be your Rosetta Stone for unlocking the value hidden in your unstructured data. The NewSci Insight Reservoir™ brings governance and insight to the data lake. You enjoy all the benefits of a state-of-the-art Big Data lake including access to hundreds of data connectors for ingesting information; transformation tools for quality assurance and data enhancement; and cataloging of your data down to the field level while at the same time having unmatched data governance capabilities: Unlike a passive data lake, the NewSci Insight Reservoir™ is a powerful cognitive computing platform where you can perform machine learning; deep learning; and natural language processing on all your structured and unstructured data. NewSci NLP connects directly to your NewSci Insight Reservoir™ to extract meaning from your text and make it available for analysis. Machine and Deep Learning algorithms can be created, and perfected, as data enters the Insight Reservoir™, increasing the value in real-time. And all of the insights can easily be made available for visualization tools including Tableau®, Qlik®, and MS Power- BI®. Jump out of the data lake and get your organization into the NewSci Insight Reservoir™

    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.

    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

    Alibaba Cloud Elastic MapReduce (E-MapReduce) is a big data processing solution to quickly process huge amounts of data. Based on open source Apache Hadoop and Apache Spark, E-MapReduce flexibly manages your big data use cases such as trend analysis, data warehousing, and analysis of continuously streaming data

    Alibaba MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing. MaxCompute supports various data importing solutions and distributed computing models, enabling users to effectively query massive datasets, reduce production costs, and ensure data security

    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.

    AMR Win Control offers software for data acquisition and measured data processing.

    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.

    Cask is an open source software company bringing virtualization to Hadoop data and apps.

    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.

    DNIF offers a comprehensive solution based on a Big Data platform that offers an end-to-end capability of processing unstructured log data, identify patterns using high speed analytics and detect complex threats.

    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

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

    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.