Dealing with Big Data
Caching and data operations such as sorting, page, grouping is performed at the database server layer, utilizing the power of database engines in dealing with the challenges of “Big Data”. This is in contrast with other frameworks which are client (web browser, windows desktop, phone app) or web server intensive operations. Nebula provides stellar performance, and the ability to perform long running operations, share data between different pages in a large application.
Nebula Framework extensively uses OO approach within the SQL Server relational database layer supporting encapsulation, abstraction, inheritance and polymorphism. This unique approach eliminates a lot of code development (no-code approach), and relates many data elements in a big data environment.
Some features built for big data are:
- Quick search to search on all fields in the page.
- Search capability: A variety of search capability is available to find the data across the system.
- Data storage partitions and archival: Data partitions are created for all the financial transactions of the customers, so that customer financial transactions can be automatically archived out after x years, but still available for viewing.
- Business Intelligence tools: New capabilities are available for data analysis and rapid building of Dashboards.
Powerful Web UI capabilities for Big Data
The underlying architecture and UI is designed specifically meant to work with “Big Data”, and to provide best UX for Big Data. When working with enterprise cloud applications that handles large volume of data, the challenge is to provide reasonable performance for all users with variety of web browsers, devices and screen sizes, internet speeds, and available resources (e.g. memory). The underlying architecture provides a lightweight or minimal load on web browsers. Minimal data transmitted between web/database server on the cloud to the web browser, provides higher performance and lower resource usage by the web browser.