A More Efficient Spark

SparkPLUS is aimed at improving the efficiency of Spark, one of the fastest growing big data open source analytic tools currently available. While Spark provides a host of analytic capabilities within a single ecosystem, its memory-heavy design means memory outages are all too common.

By integrating Spark with UniConnect, SparkPLUS offers analysts an elegant way to lift Spark’s capabilities. This integration enables only the unified data needed for analytics to be pulled into Spark, thereby vastly multiplying  its computing space.


Scaled Out Transformations

Like other ETL (Extract, Transform, Load) solutions, ScalETL automates the flow of data from a source to a target database, having converted the data into the required state.

However, unlike other ETL tools, ScalETL’s integration with UniConnect means it connects to more than 50 connectors, is highly configurable, and tracks end-to-end dataflow via a single web-based user interface. This is possible with maximum scalability and performance through the use of clustering technology.

Unified API XS

APIs Joined In Memory

Application Program Interfaces (APIs) are enabling organisations to easily open their data to, and access data from, a range of external parties. For example, developers can use the GoogleMaps API to embed Google maps on webpages, and YouTube APIs to integrate YouTube videos.

However, to derive maximum value, it is often necessary to combine the data across multiple APIs. It may also be useful to combine data sourced from an API (e.g. Google Maps) with real time data (e.g. a customer’s location), and pre-stored data (e.g. a customer’s buying patterns). The Unified API XS solution helps organisations to establish a single view of this multi-sourced data in memory, thereby super-charging processing speeds and reducing security risks. This solution can be further scaled by deploying advanced processors.