“We are very excited about today’s news. Couchbase and Spark are uniquely capable of providing the scale and performance that Big Data requires,” said Will Gardella, director of Big Data product management at Couchbase. “The Spark data processing engine and Couchbase NoSQL database are a natural fit to perform end-to-end, real-time data analytics. Integrating these two memory-centric technologies via the Couchbase Spark Connector provides a compelling Big Data solution that can dramatically improve overall business success for Digital Economy businesses.”
Web, mobile and IoT applications store and process ever increasing, massive amounts of data that when effectively leveraged, can deliver great customer experiences and create enormous competitive advantage. To achieve these benefits, businesses must have an analytical platform, like Spark, that can quickly and scalably extract data insights, and an operational database platform, like Couchbase, that can quickly and scalably turn those insights into actions. Because of the tremendous data volume and variety, the analytical and database platforms must be highly flexible, scalable and efficiently integrated together.
“By combining the power of open source Apache Spark with Couchbase, organisations will be able to exponentially increase the value derived from their Big Data,” said John Tripier, senior director of business development at Databricks. “We are excited to see Couchbase extending the power of Apache Spark, by making it easier and faster for their customers to gain performance advantages from the insights they derive from their Big Data initiatives.”
The Couchbase Spark Connector provides a flexible, efficient, open source integration between both of these best-of-breed technologies. The Couchbase Spark Connector enables ultra-fast streaming data exchange between the two platforms – reducing time to insight and time to action. In short, Couchbase NoSQL database together with Apache Spark stream processing enables applications to get smarter, faster. Examples of use cases that benefit from the Couchbase Spark Connector include:
- Real-time product recommendations. eCommerce applications suggest products to customers using proprietary, complex analytics that trigger recommendations, promotions or discounts.
- Failure detection. IoT sensor-driven applications evaluate and predict component failures using complex machine learning algorithms and streaming analytics on real-time data, which in turn can generate corrective actions, notifications and alerts.
- Network intrusion detection. Network monitoring systems detect potential security threats using ETL and analytics over metadata and historical access logs, subsequently taking immediate protective action.
- Fraud detection. Fraud detection applications compare questionable transactions to known statistical models using analytics and machine learning, and rating them.
- Product and customer 360. Comprehensive product and customer management tools aggregate data from multiple sources into a single unified repository, thereby providing a 360 degree view not previously available from the source repositories.
