For the Data Engineer, Xcalar offers self-service data wrangling without coding. Point Xcalar Data Prep to raw data in the cloud or on-prem, cleanse/transform/validate the quality of the data visually, then output the refined data back to storage for later downstream use by other applications, databases, or visualization/reporting tools.
With Xcalar Virtual Data Warehouse, DBAs point Xcalar Design to raw or refined data on-prem or in cloud storage, then visually create, manage, and maintain a virtual data warehouse that seamlessly interfaces with leading third-party applications, databases, and visualization/reporting tools. Available both on-prem and and on-cloud.
Data Scientists and Analysts become self-sufficient with Xcalar Data Science. They can visually explore petabytes of raw or refined data, and visually build sophisticated algorithms and models to discover deep insights for their business. Also available is deep integration with Google TensorFlow and other Machine Learning libraries.
Today's data-driven business needs fault tolerant, real-time operational analytics on ever-expanding quantities of data. Xcalar's unprecedented power and performance enable answers to questions that were previously impossible to ask. Xcalar delivers push-button deployment of complex dataflows created by data engineers, data scientists or analysts, for daily operational use in streaming, micro-batch, or batch mode to run in petabyte scale production environments.
When extreme data analytics is called for, Xcalar TeraRow is in a league of its own. TeraRow is the only solution that can handle native relational operations such as joins and group-bys on a trillion row dataset in interactive time.