Apache Spark vs. Oracle Big Data Service vs. Oracle Data Service Integrator vs. django-mysql Comparison Chart

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

Oracle Data Service Integrator provides companies the ability to quickly develop and manage federated data services for accessing single views of disparate information. Oracle Data Service Integrator is completely standards-based, declarative, and enables re-usability of data services. Oracle Data Service Integrator is the only data federation technology that supports the creation of bidirectional (read and write) data services from multiple data sources. In addition, Oracle Data Service Integrator offers the breakthrough capability of eliminating coding by graphically modeling both simple and complex updates to heterogeneous data sources. Install, verify, uninstall, upgrade, and get started with Data Service Integrator. Oracle Data Service Integrator was originally known as Liquid Data and AquaLogic Data Services Platform (ALDSP). Some instances of the original names remain in the product, installation path, and components.