Zoomdata is designed to push query processing to the source as much as possible.
Common analytic processing includes:
But some sources do not support even these basic types of analytic processing. If you are working with raw data in a file system or in Amazon Web Services S3, the file system will not support any kind of analytic processing.
Zoomdata includes the ability to read these raw files into Spark, where they become fast, interactive, and queryable. When establishing a connection, users can choose to “SparkIt” and preload data into a Spark dataframe for interactive use through Zoomdata. This capability is available for common file formats such as CSV files, tab-delimited files, JSON and XML files.
SparkIt can also be used for sources other than raw files. Even relational data from Oracle, SQL Server, MySQL, or data from any “slow” source can be loaded into Zoomdata’s Spark layer to convert it to a fast, queryable, interactive data source.
Zoomdata includes the ability to read raw flat files into Spark, where they become fast, interactive, and queryable.