A new software application has simple requirements for a database.
The database needs to be written to and read from. The database fulfills simple needs such as storing user information and providing the application frontend with the necessary data to render a simple webpage of financial transactions or blog posts.
As an application becomes successful, the database grows in size. The complexity of queries increases, requiring more sophisticated logic in order to maintain performance. New databases need to be added to the overall system, as users begin to have demands for advanced features such as search, or analytics.
Over time, the requirements for a database expand into a need for a data platform. A data platform might include multiple databases such as a NoSQL database, a relational database, a data warehouse, and a search index. The relationships between these different databases can vary in terms of consistency requirements, latency, and scalability.
Andrew Davidson is the Director of Cloud Products at MongoDB. In a previous episode, Andrew discussed the tradeoffs of scaling databases while maintaining high performance indexing. Andrew returns to the show to discuss the emerging subject of “data platform.”
As a growing number of companies have data requirements beyond that of a simple transactional database, Andrew’s work has increasingly involved figuring out the best ways for developers to adapt those transactional systems to providing a wider set of functionality. Full disclosure: MongoDB is a sponsor of Software Engineering Daily.
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