Apache Phoenix vs. Apache Spark vs. MySQL vs. dbForge Data Compare for 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.

dbForge Data Compare for MySQL is a fast, easy-to-use tool to compare and synchronize data of MySQL, MariaDB and Percona databases. The tool provides clear view of differences between data, allows analyzing them, generates synchronization script and applies changes at a glance. It also allows scheduling regular MySQL data comparisons using command line. Key Features: * AI Assistant integration * Support of all MySQL versions * Support of MariaDB * Percona Support * Custom mapping of tables, columns, and views * Convenient comparison wizard * Full control of data synchronization * Integrated SQL editor * Code completion and SQL Code Formatter. These features offer the extended list of suggestions during the typing of SQL code and object information on different database objects. Profile formatting capabilities allow users to create new profiles and edit the existing ones easier than ever