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:
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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.
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 d
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.
About IBM Db2 IBM believes in unlocking the potential of your data, not throttling it. We hold our databases to a higher standard, making it easy to deploy your data wherever it's needed, fluidly adapting to your changing needs and integrating with multiple platforms, languages and workloads. IBM Db2 is supported across Linux, Unix, and Windows operating systems.
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 s
Snowplow is an enterprise-grade data collection platform for companies who demand high-quality, real-time event data, delivered by a cloud-native data pipeline they fully control. 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. Our customers have full control and complete ownership of their data collection infrastructure; they have their data data pipeline in the
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.
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.
HVR is a real-time data replication solution designed to move large volumes of data FAST and efficiently in hybrid environments for real-time analytics. Our goal is to keep your data continuously moving and in sync, as you adopt new technologies for storing, streaming, and analyzing data. Our scalable solution gives you everything you need for efficient data integration from beginning to end so that you can readily revolutionize your business. HVR supports commonly used platforms such as SQL Ser
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.
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
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
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
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 conf
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
Bluemetrix Data Manager is a suite of modules automating the ingestion, transformation and governance of data on Hadoop. Data Manager provides a fully interactive drag and drop interface allowing dynamic workflow creation for the ingest & transformation of data. The suite is built on BMC’s Control-M.
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.