A buyer's guide to selecting the right big data analytics software
A collection of articles that takes you from defining technology needs to purchasing options
The KNIME Analytics Platform is an open source data analytics, reporting and integration platform developed and supported by KNIME.com AG. Through the use of a graphical interface, KNIME enables users to create data flows, execute selected analysis steps and review the results, models and interactive views.
Written in Java and built on Eclipse, the KNIME Analytics Platform leverages Eclipse's module extension capability through the use of plug-ins and connectors. Available plug-ins support the integration, with methods for text mining, image mining and time series analysis.
KNIME also integrates various other open source projects, including machine learning algorithms from Weka, R and JFreeChart. It supports wrappers to call other code, and provides nodes so users can run Java, Python, Perl and other code fragments. The KNIME Analytics Platform leverages the Eclipse plug-in capability; as a result, more than 1,000 modules exist that support connectors for all major file formats and databases, as well as a wide range of data types, statistical functions, and advanced predictive and machine learning algorithms.
In addition to the open source KNIME Analytics Platform, KNIME offers additional commercial product categories.
Cloud Analytics Platform provides users with access to KNIME Analytics Platform running in Microsoft's Azure cloud environment. The KNIME Personal Productivity Extensions include:
- KNIME Personal Productivity, which provides users with a way to efficiently build and maintain KNIME workflows, so code snippets and meta nodes in a workflow can more easily be managed, reused and shared.
- KNIME Partner Productivity, which provides consulting organizations with the ability to encrypt and lock encapsulated meta nodes to be shared with clients while protecting their intellectual property.
KNIME Performance Extensions include:
- KNIME Big Data Extensions, which provide connectors and extensions for integrating with Apache Hadoop and Spark.
- KNIME Cluster Executor, which enables KNIME Analytics Platform to be connected to a high-performance cluster and to execute a workflow distributed across the cluster.
KNIME Collaboration Extensions include:
- KNIME Server Lite, which provides collaboration capabilities such as basic user authentication and user rights, remote scheduled execution, report generation, shared data space, workflow repository, and meta nodes and priority updates.
- KNIME Server 4.4, which adds advanced features to the Server Lite extension, including more advanced user authentication and user rights, web services support, workflow versioning and commercial support.
KNIME TeamSpace improves team collaboration efforts by providing a means for storing data flows and analysis workflows centrally, to be shared and worked on collaboratively by multiple team members.
KNIME WebPortal is an available extension to Server Lite that enables users to provide web browser access to workflow results.
KNIME Cloud Server is a bundle of advanced KNIME Server features packaged for deployment in a cloud environment.
Version 3.3 of the KNIME Analytics Platform boasts several enhancements, including curved connection lines in the workflow editor, improved Excel integration to support very large files, the use of the Eclipse Neon 4.6 integration of Apache Tika for improved text mining capabilities, new cloud connector nodes for Amazon Simple Storage Service and Azure Blob Store, and improvements to deep learning nodes.
Executable versions of the KNIME Analytics Platform are available for Microsoft Windows and Linux, both 32- and 64-bit, as well as macOS.
KNIME licensing and pricing
KNIME commercial extensions are available from KNIME.org, as well as other partners and resellers. KNIME support is generally provided through online forums and community support. Additional support is available from KNIME with the purchase of the KNIME Server commercial extension. KNIME also provides other contracts for support.
The worst mistakes you can make when deploying big data analytics tools
Big data software plays major role for data warehouse projects