Big data is not a single product or component – it’s an umbrella of technologies and products. You can't really harness the power of big data with a single product. You need a solution that encompasses multiple technologies, and a toolbox to integrate them.
While every big data solution is intrinsically different, the requirements are largely the same: a) ingest high velocity data, b) store large volumes of it, and c) extract information from it. Depending on the solution, low latency, performance, and throughput can be key requirements.
The most innovative big data solutions use streaming to move operational data between ingestion points, storage systems and analytical platforms. Any big data solution will need a scalable, high performance database. What else will be required? That's up to you.
Connectors
Spark
Accelerate your Spark workloads and publish results using Couchbase Server. Add ETL, analytics, and machine learning to your Couchbase applications with full support for Spark Core, Spark SQL, and Spark Streaming. Now available with support for Spark 2.1, including the Structured Streaming API.
Kafka
Use Couchbase as either a consumer or producer with Kafka message queues. Continuously stream data between Couchbase and Kafka as it is generated. Now available with support for Kafka Connect, which standardizes management, enables end-to-end monitoring, and supports dashboard tools such as Confluent Control Center.
Hadoop
Combine Hadoop’s big data scalable data processing with Couchbase Server’s operational data centric applications. Built-in support for Sqoop, Storm, etc. Co-developed with Cloudera and certified by Hortonworks.