SAP HANA and Apache Spark: Together at Last

Companies that want to accelerate their digital transformation may be consider either SAP HANA or Apache Spark as their big data processing environment. Now there’s no need to choose! SAP HANA can integrate with Apache Spark so your business can benefit from the unique features of each solution.

Back in 2014, Databricks, the company behind Apache Spark, announced a powerful alliance between the two solutions. Working together, SAP HANA and Apache Spark streamline the way companies access and process contextual data stored in various places across the business.

Both SAP HANA and Apache Spark serve the same basic function, but each have unique features. The new integration allows them to complement each other in providing your business with an even more comprehensive approach to big data management and analytics.

Commonalities in Data Processing

At first glance, comparing SAP HANA to Apache Spark may seem like comparing apples to apples. SAP HANA and Apache Spark both equip companies for big data analytics with in-memory computing and a combination of transactional and analytics data processing. In-memory computing speeds up data processing by allowing your team to access data without having to go to disk. Eliminating latency and bottlenecks is the key to gaining real-time insights from data.

Both environments allow organizations to process live data for actionable insights using predictive analytics and machine learning. Not only can your business forecast trends, but the partnership between SAP HANA and Apache Spark allows tons of both structured and unstructured data to be processed to draw new hypotheses.

SAP HANA and Apache Spark each provide a platform that enables your company to develop applications for analytics that can be tailored to meet specific company goals. Applications can be designed for the web or mobile to help you better understand customer and client needs and behaviors.

What SAP HANA Brings to the Table

A closer look at both data-processing environments, however, shows that they each bring something different to the partnership. SAP HANA has additional built-in features that increase efficiency and security. It offers data management tools for storage tiering, or moving information to the proper type of storage based on frequency of access. Other SAP HANA data management tools reduce redundancy, lessening the demand for extra storage capacity.

SAP HANA’s security tools simplify administration and monitoring processes that can dominate your team’s time and attention. Built-in business continuity and security tools include encryption, identity and access management, a security dashboard, and disaster recovery solutions.

Expanding the Reach of SAP HANA With Apache Spark

While SAP HANA brings a variety of features to the partnership, Apache Spark provides its own resources and capabilities. Apache Spark is an open source solution that was developed through the collaboration of 200 companies. In partnership with Apache Spark, SAP HANA can benefit from open source innovations, including cutting-edge analytics applications.

On its own, SAP HANA cannot work through cluster computing to allow for parallel processing. That’s where Apache Spark comes in. Parallel processing is ideal for high-throughput applications such as those required to analyze IoT data. Apache Spark is scalable and ideally suited for high availability and high performance computing.

Most importantly, through its integration with Apache Spark, SAP HANA gains the ability to draw from data in Hadoop for a complete view of all your company’s data. This includes access to contextual, historical, and operational data from ERP and CRM systems. Access to all your data means making fully-informed decisions for a better chance at positive results.

Not only can you access more data more easily, but you have more options for mining insights from data. SAP HANA and Apache Spark have complementary sets of data analytics tools. SAP HANA includes predictive algorithms as well as the ability to build applications that combine the textual and spatial analytics needed to make sense of unstructured data. Apache Spark offers machine learning algorithms and transforms data into graphs so trends can be easily visualized.

Choosing the Right Hardware for Your Integration

Now that SAP HANA and Apache Spark are integrated, moving to IBM POWER makes even more sense. IBM has developed a data engine specially designed for Hadoop and Apache Spark. Like all IBM’s Power Systems, the IBM Data Engine is designed to meet the high-performance requirements of big data. The Data Engine includes POWER8 technology with 8 to 10 cores per socket and 8 threads per core.

Unique to other Power Systems, this particular solution is preconfigured and pre-tested to work with Apache Spark’s cluster computing. Pairing SAP HANA and Apache Spark takes your data processing to another level. Running both solutions on POWER will launch you into the stratosphere of success.

Originally published at on May 25, 2017.

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