2 Integrations with IBM Db2 Event Store

View a list of IBM Db2 Event Store integrations and software that integrates with IBM Db2 Event Store below. Compare the best IBM Db2 Event Store integrations as well as features, ratings, user reviews, and pricing of software that integrates with IBM Db2 Event Store. Here are the current IBM Db2 Event Store integrations in 2026:

  • 1
    IBM Cloud Pak for Data
    The biggest challenge to scaling AI-powered decision-making is unused data. IBM Cloud Pak® for Data is a unified platform that delivers a data fabric to connect and access siloed data on-premises or across multiple clouds without moving it. Simplify access to data by automatically discovering and curating it to deliver actionable knowledge assets to your users, while automating policy enforcement to safeguard use. Further accelerate insights with an integrated modern cloud data warehouse. Universally safeguard data usage with privacy and usage policy enforcement across all data. Use a modern, high-performance cloud data warehouse to achieve faster insights. Empower data scientists, developers and analysts with an integrated experience to build, deploy and manage trustworthy AI models on any cloud. Supercharge analytics with Netezza, a high-performance data warehouse.
    Starting Price: $699 per month
  • 2
    Apache Parquet

    Apache Parquet

    The Apache Software Foundation

    We created Parquet to make the advantages of compressed, efficient columnar data representation available to any project in the Hadoop ecosystem. Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. We believe this approach is superior to simple flattening of nested namespaces. Parquet is built to support very efficient compression and encoding schemes. Multiple projects have demonstrated the performance impact of applying the right compression and encoding scheme to the data. Parquet allows compression schemes to be specified on a per-column level, and is future-proofed to allow adding more encodings as they are invented and implemented. Parquet is built to be used by anyone. The Hadoop ecosystem is rich with data processing frameworks, and we are not interested in playing favorites.
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