In this section we are going to discuss about the Big Data platform and Big Data tools in detail which can be used in the Enterprise environment for handling huge data sets. We will introduce you with the major Big Data platform and various tools used in such environment.
What is Big Data Platform?
Big Data Platform is integrated IT solution for Big Data management which combines several software system, software tools and hardware to provide easy to use tools system to enterprises.
It is a single one-stop solution for all Big Data needs of an enterprise irrespective of size and data volume. Big Data Platform is enterprise class IT solution for developing, deploying and managing Big Data.
There are several Open source and commercial Big Data Platform in the market with varied features which can be used in Big Data environment.
Features of Big Data Platform
Here are most important features of any good Big Data Analytics Platform:
What is Hadoop?
Hadoop is open-source, Java based programming framework and server software which is used to save and analyze data with the help of 100s or even 1000s of commodity servers in a clustered environment. Hadoop is designed to storage and process large datasets extremely fast and in fault tolerant way. Hadoop uses HDFS (Hadoop File System) for storing data on cluster of commodity computers. If any server goes down it know how to replicate the data and there is no loss of data even in hardware failure.
Hadoop is Apache sponsored project and it consists of many software packages which runs on the top of the Apache Hadoop system. Check more details at Big Data tutorials section.
Hadoop provides set of tools and software for making the backbone of the Big Data analytics system. Hadoop ecosystem provides necessary tools and software for handling and analyzing Big Data. On the top of the Hadoop system many applications can be developed and plugged-in to provide ideal solution for Big Data needs.
Cloudra is one of the first commercial Hadoop based Big Data Analytics Platform offering Big Data solution. Its product range includes Cloudera Analytic DB, Cloudera Operational DB, Cloudera Data Science & Engineering and Cloudera Essentials. All these products are based on the Apache Hadoop and provides real-time processing and analytics of massive data sets.
Amazon Web Services
Amazon is offering Hadoop environment in cloud as part of its Amazon Web Services package. AWS Hadoop solution is hosted solution which runs on Amazon’s Elastic Cloud Compute and Simple Storage Service (S3). Enterprises can use the Amazon AWS to run their Big Data processing analytics in the cloud environment.
Amazon EMR allows companies to setup and easily scale Apache Hadoop, Spark, HBase, Presto, Hive, and other Big Data Frameworks using its cloud hosting environment.
Hortonworks is using 100% open-source software without any propriety software. Hortonworks were the one who first integrated support for Apache HCatalog. The Hortonworks is a Big Data company based in California. This company is developing and supports application for Apache Hadoop. Hortonworks Hadoop distribution is 100% open source and its enterprise ready with following features:
MapR is another Big Data platform which us using the Unix file system for handling data. It is not using HDFS and this system is easy to learn anyone familiar with the Unix system. This solution integrates Hadoop, Spark, and Apache Drill with a real-time data processing feature.
IBM Open Platform
IBM also offers Big Data Platform which is based on the Hadoop eco-system software. IBM is well know company in software and data computing. It uses the latest Hadoop software and provides following features (IBM Open Platform Features):
The Microsoft HDInsight is also based on the Hadoop distribution and it’s a commercial Big Data platform from Microsoft. Microsoft is software giant which is into development of windows operating system for Desktop users and Server users.
This is the big Hadoop distribution offering which runs on the Windows and Azure environment. It offer customized, optimized open source Hadoop based analytics clusters which uses Spark, Hive, MapReduce, HBase, Strom, Kafka and R Server which runs on the Hadoop system on windows/Azure environment.
Intel Distribution for Apache Hadoop
Intel also offers its package distribution of Hadoop software which includes company’s Graph builder and Analytics toolkit.
This distribution can be purchased with various channel partners and come with support and yearly subscription.
Datastax Enterprise Analytics
Datastax Enterprise Analytics is another play in the Big Data Analytics platform which offers its own distribution which is based on Apache Cassandra database management system which runs on the top of Apache Hadoop installation. It also included propriety system with a dashboard which is used for security management, searching data, dashboard for viewing various details and visualization engine.
It can handle analysis of 10 million data points every second, so it’s a powerful system.
Teradata Enterprise Access for Hadoop
Teradata Enterprise Access for Hadoop is another player into Big Data Platform and it offers package Hadoop distribution which again based on Hortonworks distribution. Teradata Enterprise Access for Hadoop offers Hardware and software in its Big Data solution which can be used by enterprise to process its data sets.
as part of its package solution.
Pivotal HD offers is another Hadoop distribution with includes includes database tools Greenplum and analytics platform Gemfire.
Indian railways, BMW, China Citic Bank and many other big players are using this distribution of Big Data Platform.
Open Source Big Data Platform
Now we will discuss various open-source Big Data Platform which can be used for Big Data handling and data analytics in real-time environment. Both small and Big Enterprise can use these tools for managing their enterprise data for getting best value from their enterprise data.
Apache Hadoop is Big Data platform and software package which is Apache sponsored project. Under Apache Hadoop project various other software is being developed which runs on the top of Hadoop system to provide enterprise grade data management and analytics solutions to enterprise. Apache Hadoop is open-source, distributed file system which provides data processing and analysis engine for analyzing large set of data. Hadoop can run on Windows, Linux and OS X operating systems, but it is mostly used on Ubunut and other Linux variants.
Check Big Data tutorials.
The MapReduce engine was originally written by Google and this is the system which enables the developers to write program which can run in parallel on 100 or even 1000s of computer nodes to process vast data sets. After processing all the job on the different nodes it comes the results and return it to the program which executed the MapReduce job. This software is platform independent and runs on the top of Hadoop ecosystem. It can process tremendous data at very high speed in Big Data environment.
GridGain is another software system for parallel processing of data just like MapRedue. GridGain is an alternative of Apache MapReduce. GridGain is used for the processing of in-memory data and its is based on Apache Iginte framework. GridGain is compatable with the Hadoop HDFS and runs on the top of Hadoop ecosystem.
Then enterprise version of GridGain can be purchased from official website of GridGain. While free version can be downloaded from GitHub repository.
HPCC Systems stands for "high performance computing cluster” and this system is developed by LexisNexis Risk Solutions. According to the company this software is much faster than Hadoop and can be used in the cloud environment.
HPCC Systems is developed in C++ and compiled into binary code for distribution. HPCC Systems is open-source, massive parallel processing system which is installed in cluster to process data in real-time.
It requires Linux operating system and runs on the commodity servers connected with high-speed network. It is scalable from one node to 1000s of nodes to provide performance and scalability.
Apache Storm is a software for real-time computing and distributed processing. Its free and open-source software developed at Apache Software foundation. It’s a real-time, parallel processing engine. Apache Storm is highly scalable, fault-tolerant which supports almost all the programming language.
Apache Strom can be used in:
Apache Strom is used by Yahoo, Twitter, Spotify, Yelp, Flipboard and many other data giants.
Apache Spark is software that runs on the top of Hadoop and provides API for real-time, in-memory processing and analysis of large set of stored in the HDFS. It stores the data into memory for faster processing.
Apache Spark runs program 100 times faster in-memory and 10 times faster on disk as compared to the MapRedue. Apache Spark is here to faster the processing and analysis of big data sets in Big Data environment.
Apache Spark is being adopted very fast by the business to analyze their data set to get real value of their data.
SAMOA stands for Scalable Advanced Massive Online Analysis, it’s a system for mining the Big Data streams. SAMOA is open-source software distributed at GitHub, which can be used as distributed machine learning framework also.
Big Data industry is growing very fast in 2017 and companies are fast moving their data to Big Data Platform. There is huge requirement of Big Data in the job market, many companies are providing training and certifications in Big Data technologies.
New engineers can learn Big Data technologies and apply for highly paying jobs.
In this section we explained you about the Big Data Platform and provided you the details of various IT solutions which are being used in Big Data environment. Based on your requirement you can choose from these technologies. If you are enterprise customer and looking for companies for Big Data software development the contact us by visit Big Data Application Development Services url.
Big Data Tutorials
Explore the Big Data technologies through following tutorials and articles:
Rs. 20,000 US$ 300
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Course Duration: 30 hrs
Posted on: April 6, 2017 If you enjoyed this post then why not add us on Google+? Add us to your Circles