Why adopt an open-source and unified-analytics platform?
An open and unified analytics platform reduces risk and protects your investment.
IBM and Hortonworks provide a data analytics platform with the necessary tools to easily incorporate and analyze data from open source, IBM and non-IBM systems. It includes premium offerings and services built on open-source Apache Hadoop, delivering extra value without proprietary lock-in.
IBM participates in the ODPi nonprofit Linux Foundation project, building on standard Hadoop interfaces so you can easily add capabilities from multiple sources.
Open-source capabilities
Hortonworks Data Platform
A security-rich, enterprise-ready open-source Hadoop distribution based on a centralized architecture
IBM Db2® Big SQL
An enterprise-grade, hybrid ANSI-compliant SQL on Hadoop engine, delivering massively parallel processing (MPP) and advanced data query
IBM Watson® Studio
A collaborative, configurable environment for data scientists to analyze data using RStudio®, Jupyter and Python
IBM Data Management Platform for MongoDB Enterprise Advanced
A robust, scalable, highly available document-database solution to support mission-critical deployments
In the spotlight
Data lake
Use a data lake to gather, store and analyze your structured, semi-structured and unstructured data and to facilitate the extraction of actionable insights.
Resources
Build a better data lake
Discover best practices to follow and the potential pitfalls to avoid when integrating a data lake into your existing data infrastructure. Learn how enterprise-grade security and governance can allow any business to leverage a growing diversity of data to drive innovation across the organization.
The Power of One: IBM + Hortonworks
Discover how IBM and Hortonworks can combine to form an enterprise-ready Hadoop solution that benefits your organization’s analytics.
IBM Db2 Big SQL
Learn more about the features and capabilities of Db2 Big SQL, and how to make better decisions fast with powerful SQL-on-Hadoop for big data analytics.