News

After Spark-Based Revamp, IBM Launches New Data Services

• By David Ramel
• February 4, 2016

IBM last summer made big news by going all in on Apache Spark for Big Data analytics, with a massive developer investment that resulted in redesigned data products and today's launch of a bevy of new services running on its cloud.

With them, the company now boasts more than 25 offerings in its Cloud Data Services, described as "a portfolio of self-service, composable data and analytics services for the developer, data science professional and analytics architect." IBM said they were designed to help developers build, deploy and manage Web and mobile apps, while data scientists can use them to discover hidden trends using cloud-based data and analytics.

And now they're leveraging Spark technology, often described as the most popular open source project. IBM in June hopped on the Spark bandwagon in a big way -- promising to put more than 3,500 researchers and developers to work on related projects at labs around the world -- while calling it "potentially the most significant open source project of the next decade."

Big Blue said the new services announced today build on its Spark investment, which has seen more than 25 of its core analytics and commerce solutions get a Spark-based redesign to boost real-time processing functionality.

Along with those redesigned products, the new data services running on its Bluemix cloud service include:

• Compose Enterprise, to help development teams build modern Web-scale apps faster by enabling them to deploy business-ready open source databases in minutes on their own dedicated cloud servers.
• Graph, a managed graph database service built on Apache TinkerPop that provides developers a complete stack to extend business-ready apps with real-time recommendations, fraud detection, Internet of Things (IoT) and network analysis uses.
• Predictive Analytics, a service that lets developers self-build machine learning models from a broad library into applications to help deliver predictions for specific product use cases, without the help of a data scientist.
• Analytics Exchange is an open data exchange that includes a catalog of more than 150 publicly available datasets that can be used for analysis or integrated into applications.

"Data is the common thread within the enterprise, regardless of where its source might be," said IBM exec Derek Schoettle in a statement. "In the past, data handlers have relied on disparate systems for data needs, but our goal is to move data into the future by providing a one-stop shop to access, build, develop and explore data. IBM's integrated Cloud Data Services give developers greater scalability and flexibility to build, deploy and manage Web and mobile cloud applications, and enable data scientists to apply information across businesses efficiently."