While Zoomdata excels with big data, Zoomdata is not only for big data. Enterprises have significant data assets in relational databases, data warehouses, and other traditional systems. For this reason, Zoomdata also enables data discovery with SQL sources such as Teradata, Oracle, SQL Server, PostgreSQL, MySQL, and Amazon Aurora.
Many of these systems are built on column-store and/or massively parallel processing (MPP) architectures that can handle significant volumes of data.
Zoomdata features certified support for the Teradata Database (on-premise), Teradata Database on AWS, as well as the Teradata Appliance for Hadoop on Cloudera CDH and Hortonworks HDP.
Enterprise data architectures almost always contain a combination of traditional sources like SQL and MPP databases as well as modern sources like Apache Hadoop and Apache Spark. Zoomdata enables exploration across all these data sources.
The unique features of Zoomdata that support visual analytics for big data can also be applied to traditional data. For example, Zoomdata Fusion can combine modern and traditional sources without having to move data to a common data store. Data sharpening, micro-queries, result set caching, and Data DVR all add an extra dimension to creating visual analytics via traditional data sources.
Zoomdata enables data discovery with SQL sources such as Oracle, SQL Server, PostgreSQL, MySQL, and Amazon Aurora.