Today’s market is flooded with an array of Big Data tools. They bring cost efficiency, better time management into the data analytical tasks. Here is the list of best big data tools with their key features and download links.

1) Hadoop:

The Apache Hadoop software library is a big data framework. It allows distributed processing of large data sets across clusters of computers. It is designed to scale up from single servers to thousands of machines.

Features:

Authentication improvements when using HTTP proxy server

Specification for Hadoop Compatible Filesystem effort

Support for POSIX-style filesystem extended attributes

It offers robust ecosystem that is well suited to meet the analytical needs of developer

It brings Flexibility In Data Processing

It allows for faster data Processing

Download link: https://hadoop.apache.org/releases.html

2) HPCC:

HPCC is a big data tool developed by LexisNexis Risk Solution. It delivers on a single platform, a single architecture and a single programming language for data processing.

Features:

Highly efficient accomplish big data tasks with far less code.

Offers high redundancy and availability

It can be used both for complex data processing on a Thor cluster

Graphical IDE for simplifies development, testing and debugging

It automatically optimizes code for parallel processing

Provide enhance scalability and performance

ECL code compiles into optimized C++, and it can also extend using C++ libraries

Download link: https://hpccsystems.com/try-now

3) Storm:

Storm is a free and open source big data computation system. It offers distributed real-time, fault-tolerant processing system. With real-time computation capabilities.

Features:

It benchmarked as processing one million 100 byte messages per second per node

It uses parallel calculations that run across a cluster of machines

It will automatically restart in case a node dies. The worker will be restarted on another node

Storm guarantees that each unit of data will be processed at least once or exactly once

Once deployed Storm is surely easiest tool for Bigdata analysis

Download link: http://storm.apache.org/downloads.html

4) Qubole:

Qubole Data is Autonomous Big data management platform. It is self-managed, self-optimizing tool which allows the data team to focus on business outcomes.

Features:

Single Platform for every use case

Open-source Engines, optimized for the Cloud

Comprehensive Security, Governance, and Compliance

Provides actionable Alerts, Insights, and Recommendations to optimize reliability, performance, and costs

Automatically enacts policies to avoid performing repetitive manual actions

Download link: https://www.qubole.com/

5) Cassandra:

The Apache Cassandra database is widely used today to provide an effective management of large amounts of data.

Features:

Support for replicating across multiple data centers by providing lower latency for users

Data is automatically replicated to multiple nodes for fault-tolerance

It is most suitable for applications that can’t afford to lose data, even when an entire data center is down

Cassandra offers support contracts and services are available from third parties

Download link: http://cassandra.apache.org/download/

6) Statwing:

Statwing is an easy-to-use statistical tool. It was built by and for big data analysts. Its modern interface chooses statistical tests automatically.

Features:

Explore any data in seconds

Statwing helps to clean data, explore relationships, and create charts in minutes

It allows creating histograms, scatterplots, heatmaps, and bar charts that export to Excel or PowerPoint

It also translates results into plain English, so analysts unfamiliar with statistical analysis

Download link: https://www.statwing.com/

7) CouchDB:

CouchDB stores data in JSON documents that can be accessed web or query using JavaScript. It offers distributed scaling with fault-tolerant storage. It allows accessing data by defining the Couch Replication Protocol.

Features:

CouchDB is a single-node database that works like any other database

It allows running a single logical database server on any number of servers

It makes use of the ubiquitous HTTP protocol and JSON data format

Easy replication of a database across multiple server instances

Easy interface for document insertion, updates, retrieval and deletion

JSON-based document format can be translatable across different languages

Download link: http://couchdb.apache.org/

8) Pentaho:

Pentaho provides big data tools to extract, prepare and blend data. It offers visualizations and analytics that change the way to run any business. This Big data tool allows turning big data into big insights.

Features:

Data access and integration for effective data visualization

It empowers users to architect big data at the source and stream them for accurate analytics

Seamlessly switch or combine data processing with in-cluster execution to get maximum processing

Allow checking data with easy access to analytics, including charts, visualizations, and reporting

Supports wide spectrum of big data sources by offering unique capabilities

Download link: http://www.pentaho.com/download

9) Flink:

Apache Flink is an open-source stream processing Big data tool. It is distributed, high-performing, always-available, and accurate data streaming applications.

Features:

Provides results that are accurate, even for out-of-order or late-arriving data

It is stateful and fault-tolerant and can recover from failures

It can perform at a large scale, running on thousands of nodes

Has good throughput and latency characteristics

This big data tool supports stream processing and windowing with event time semantics

It supports flexible windowing based on time, count, or sessions to data-driven windows

It supports a wide range of connectors to third-party systems for data sources and sinks

Download link: https://flink.apache.org/

10) Cloudera:

Cloudera is the fastest, easiest and highly secure modern big data platform. It allows anyone to get any data across any environment within single, scalable platform.

Features:

High-performance analytics

It offers provision for multi-cloud

Deploy and manage Cloudera Enterprise across AWS, Microsoft Azure and Google Cloud Platform

Spin up and terminate clusters, and only pay for what is needed when need it

Developing and training data models

Reporting, exploring, and self-servicing business intelligence

Delivering real-time insights for monitoring and detection

Conducting accurate model scoring and serving

Download link: https://www.cloudera.com/

11) Openrefine:

Open Refine is a powerful big data tool. It helps to work with messy data, cleaning it and transforming it from one format into another. It also allows extending it with web services and external data.

Features:

OpenRefine tool help you explore large data sets with ease

It can be used to link and extend your dataset with various webservices

Import data in various formats

Explore datasets in a matter of seconds

Apply basic and advanced cell transformations

Allows to deal with cells that contain multiple values

Create instantaneous links between datasets

Use named-entity extraction on text fields to automatically identify topics

Perform advanced data operations with the help of Refine Expression Language

Download link: http://openrefine.org/download.html

12) Rapidminer:

RapidMiner is an open source big data tool. It is used for data prep, machine learning, and model deployment. It offers a suite of products to build new data mining processes and setup predictive analysis.

Features:

Allow multiple data management methods

GUI or batch processing

Integrates with in-house databases

Interactive, shareable dashboards

Big Data predictive analytics

Remote analysis processing

Data filtering, merging, joining and aggregating

Build, train and validate predictive models

Store streaming data to numerous databases

Reports and triggered notifications

Download link: https://my.rapidminer.com/nexus/account/index.html#downloads

13) DataCleaner:

DataCleaner is a data quality analysis application and a solution platform. It has strong data profiling engine. It is extensible and thereby adds data cleansing, transformations, matching, and merging.

Feature:

Interactive and explorative data profiling

Fuzzy duplicate record detection

Data transformation and standardization

Data validation and reporting

Use of reference data to cleanse data

Master the data ingestion pipeline in Hadoop data lake

Ensure that rules about the data are correct before user spends thier time on the processing

Find the outliers and other devilish details to either exclude or fix the incorrect data

Download link: http://datacleaner.org/

14) Kaggle:

Kaggle is the world’s largest big data community. It helps organizations and researchers to post their data & statistics. It is the best place to analyze data seamlessly.

Features:

The best place to discover and seamlessly analyze open data

Search box to find open datasets

Contribute to the open data movement and connect with other data enthusiasts

Download link: https://www.kaggle.com/

15) Hive:

Hive is an open source-software big data too. It allows programmers analyze large data sets on Hadoop. It helps with querying and managing large datasets real fast.

Features:

It Supports SQL like query language for interaction and Data modeling

It compiles language with two main tasks map, and reducer

It allows defining these tasks using Java or Python

Hive designed for managing and querying only structured data

Hive’s SQL-inspired language separates the user from the complexity of Map Reduce programming

It offers Java Database Connectivity (JDBC) interface

Download link: https://hive.apache.org/downloads.html