Hadoop-Related Software
Hadoop-Related Software Overview
Best Hadoop-Related Software include:
Apache Spark and Amazon EMR.
Hadoop-Related Software TrustMap
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Hadoop-Related Products
(1-25 of 34) Sorted by Most Reviews
Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.
Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable…
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.
Hortonworks Data Platform (HDP) is an open source framework for distributed storage and processing of large, multi-source data sets. HDP modernizes IT infrastructure and keeps data secure—in the cloud or on-premises—while helping to drive new revenue streams, improve customer experience,…
HDInsight is an implementation of the Apache Hadoop technology stack on the Microsoft Azure cloud platform: It is based on the Hortonworks Hadoop distribution. Microsoft Azure HDInsight includes implementations of Apache Spark, HBase, Storm, Pig, Hive, Sqoop, Oozie, Ambari, etc.…
HPE Ezmeral Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform. Just as a loom weaves multiple threads…
Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.
Cloudera Manager is a management application for Apache Hadoop and the enterprise data hub, from Cloudera.
Apache Flume is a product enabling the flow of logs and other data into a Hadoop environment.
IBM offers Db2 Big SQL, an enterprise grade hybrid ANSI-compliant SQL on Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Big SQL offers a single database connection or query for disparate sources such as HDFS, RDMS, NoSQL databases, object stores…
Apache Sqoop is a tool for use with Hadoop, used to transfer data between Apache Hadoop and other, structured data stores.
Apache Drill is a schema-free query engine for use with NoSQL or Hadoop data or file storage systems and databases.
The Oracle Big Data Cloud Services features managed and secure platform cloud service for Apache Hadoop and Apache Spark delivered as an elastic, integrated platform. It provides support for streaming, batch, and interactive analysis.
Syncsort Trillium DQ for Big Data (formerly Trillium Quality for Big Data) supports enterprises using a Big Data framework like Hadoop with data quality functions like data integration, data cleansing, standardization and parsing, with prebuilt process flows that can be configured…
VMware Tanzu Greenplum (or Pivotal Greenplum, formerly from EMC) is a massively parallel processing (MPP) data platform, based on the open source Greenplum Database. The data warehouse application is supported by Pivotal Software, which is now part of VMware (acquired 2019)
Learn More About Hadoop-Related Software
What is Hadoop Software?
Hadoop is a very unusual kind of open-source data store from the Apache Foundation. However, an entire ecosystem of products has evolved around the Hadoop data store, to the point where it has become its own technology category.
The central idea of Hadoop is that data is spread across many commodity, inexpensive servers, although there are several commercial distributions of Hadoop from Cloudera and Hortonworks who wrap services around the technology.
Unlike a traditional database, Hadoop can handle huge volumes of both structured and unstructured data including log files, streaming data, images, audio and video files. All of this data can be put into the Hadoop cluster and accessed, modified and processed in place, eliminating the need to duplicate and structure data in a traditional warehouse.
Once this huge volume of structured and unstructured data has been stored, how do you extract any value from it? Since Hadoop is not a structured database, structured query languages like SQL do not work. But Hadoop has its own data processing and query framework called MapReduce. Developers can use MapReduce to write programs that can retrieve whatever data is needed. However, MapReduce has several constraints affecting performance and a newer product like Apache Spark provides an alternative distributed computing framework, which is significantly more efficient. Similarly, products like Hive and Cloudera Impala provide a SQL-like query language, which is much easier for data analysts to learn and use.