Difference between Operational and Analytical Big Data

Operational Big Data

Operational Big Data systems provide operational features to run real-time, interactive workloads that ingest and store data. It consists of real-time, transactional data generated from day-to-day activities, such as online transactions, social media feeds, and sensor readings. MongoDB is a top technology for operational Big Data applications with over 10 million downloads of its open source software.

Analytical Big Data

Analytical Big Data is a process of examining and analyzing enormous, complex datasets to find patterns, trends, and correlations, which then inform data-driven business decisions. It is very useful for retrospective, sophisticated analytics of your data. Hadoop is the most popular example of an Analytical Big Data technology.

Operational vs Analytical Big Data

ParametersOperational Big DataAnalytical Big Data
Data TypeReal-time, transactionalHistorical, batched
PurposeDaily operations, immediate actionStrategic planning, long-term growth
FocusCurrent state of eventsPatterns and trends over time
StorageDatabases, streamsData warehouses, lakes
ProcessingReal-time, interactiveRetrospective, batch-oriented