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Db2 Event Store on Cloud Pak for Data

Version 3.0.2
Included
IBM

Description

IBM Db2 Event Store is an in-memory database that is designed to handle massive amounts of structured data that is stored in Apache Parquet format. Because it is optimized for event-driven data processing and analysis, this high-speed data store can capture, analyze, and store more than 250 billion events per day. It is ideal for:

  • Internet of Things (IoT) solutions
  • Payments
  • Logistics
  • Web commerce

The data store is flexible and scalable to adapt quickly to your changing business needs. With the Db2 Event Store service, you can create these data stores in your Cloud Pak for Data cluster so that you can govern the data and use it for more in-depth analysis.

Using an integrated Db2 Event Store database can be helpful in the following situations:

  • You need to govern and catalog streaming data as it is ingested.
  • You need to search the data as it is ingested.
  • You need to rapidly ingest large amounts of streaming data (up to one million inserts per second per node) and use it for real-time analytics with integrated machine learning capabilities.

Db2 Event Store is recommended if you need to ingest data from streaming data sources or IOT devices or sensors, for example to:

  • Analyze incoming data from different medical devices in real time to provide better health outcomes for patients while providing cost savings for moving the data to storage.
  • Analyze huge volumes of data from airplane sensors in real time to ensure passenger safety.
  • Analyze large amounts of data from weather sensors in real time to make accurate weather forecasts.
  • Ingest huge volumes of trading data and trigger real-time derivative calculations that are recorded to the database.

Integrated services

Related services

Related services
Streams Develop and run applications that process in-flight data.
Watson Knowledge Catalog Create catalogs of curated assets with this secure enterprise catalog management platform that is supported by a data governance framework.