It’s probably not possible to discuss Big Data without mentioning Apache Hadoop. However, Hadoop is not the end-all, be-all of Big Data, it’s only a part of the flourishing Big Data software ecosystem. There are lots of other Big Data tools and platforms, many of which are freely available, and as opposed to paying for licenses, organizations can pay to have the open source code modified to their specific requirements, if needed. (Numerous open source big data tools are also offered on a business premise, with support offered to companies that want to use them, however, do not have the ability to utilize the source code unaided.) Let’s take a look at some of the best ones.
1. Lumify is a moderately new open source venture to make Big Data combination, examination, and perception stage. Its Web-based interface lets you find associations and look for connections in your information by means of a suite of explanatory choices, including 2D and 3D diagram representations, full-message faceted pursuit, dynamic histograms, intelligent geographic maps and community oriented workspaces.
2. Talend Open Studio for Big Data gives you a chance to work with Hadoop and NoSQL databases. It is one of the big data tools which provides basic graphical apparatuses and wizards to create local code that helps you influence the full force of Hadoop.
3. HPCC Systems Big Data is a platform for controlling, changing, questioning and data warehousing your Big Data, and is an alternative to Hadoop. It is one of the big data tools that utilizes the Thor data refinery, Roxie data query/delivery engine, and Enterprise Control Language (ECL) as an alternative to Apache Pig. (ECL is asserted to be 4.45 times speedier than Pig by and large.) The Community Edition is a free version of the HPCC Systems platform and is bolstered by a dynamic group of designers and other enthusiasts by means of online discussion forums.
4. Apache Storm is a distributed constant calculation framework that permits you to prepare unbounded surges of information dependably. It is one of the big data tools that accomplishes for real-time processing what Hadoop accomplishes for batch processing. You can use the product with any programming language.
5. Apache Drill is an SQL inquiry engine for Big Data exploration. It is one of the big data tools that has been designed from the very start to bolster superior investigation on your semi-organized and quickly advancing information originating from present-day Big Data applications. It also provides plug and play incorporation with your current Apache Hive and Apache HBase organizations.
6. Apache Samoa (Scalable Advanced Massive Online Analysis) is a platform for mining your Big Data streams. It is one of the big data tools with a distributed spilling machine learning (ML) system that contains a programming abstraction for distributed streaming ML algorithms. This lets you develop new ML calculations without directly having to go through the complexity of underlying distributed stream processing engines (DSPEs), for example, Apache Storm, Apache S4, and Apache Samza.
7. Ikanow is a little different: It is one of the big data tools that claims to be the world’s first unstructured security analytics platform. The free Community Edition gives you a chance to take advantage of unstructured and structured data and provides ingest, search, data widgets and export options in an open, self-supported platform.
8. Apache Solr is made to be highly reliable, versatile, and fault tolerant, with features like distributed indexing, replication, and load-balanced querying, automated failover and recovery, centralized configuration, and other features. Solr powers the search and navigation features of a several of the world’s biggest Internet websites, and is based on Apache Lucene‘s Java-based indexing and search technology.
9. Elasticsearch is a distributed, open source search and exploration engine, built for horizontal scalability, reliability, and easy handling. It is one of the big data tools that incorporates the speed of search with the power of analytics by means of a query language that has been built to be developer friendly, covering structured, unstructured and time-series data.