Offload Legacy Data, Hassle-Free

Diyotta helps organizations become more agile in processing large volumes of data, enabling advanced analytics on historical data.

Build a Modernized & Sustainable ETL Offload Solution for Hadoop With Inbuilt Best Practices

Organizations suffer from high ETL complexities, costs, data latency and redundancy when they go through a data warehouse modernization. Diyotta uses Hadoop as an enterprise data hub to reduce traditional enterprise data warehouse costs and improve performance. This offers a scope of faster ingestion and data integration of all forms of data – structured and unstructured – and can run multiple transformation jobs and deliver information to multiple systems, enabling faster analytics for better insights.

  • Cuts down ETL complexity
    and increases agility

  • Unlimited scalability and
    non-latency

  • Data remains reusable
    and transparent

Diyotta – ETL Offload Solution Architecture

Enterprise Data Warehouse is a crucial component within the overall data ecosystem. The traditional ETL processing has maxed out impacting the data delivery to who needs it and suffers from performance bottlenecks. Diyotta instantly helps offload heavy ETL processing to Hadoop and improves processing time with its innovative pushdown architecture for universal big data platforms.

  • Diyotta has faster SQL based transformations
  • Improved data quality
  • Have a faster recovery with transactions.
  • Accomplish greater business agility with more readily accessible insights on your data

 

  • Value

    Significantly lower TCO (Total
    Cost of Ownership) with
    rapid development

  • Visibility

    Offers data lineage, process
    transparency, monitoring and
    impact analysis

  • Versatility

    Native data connectors, integrated
    scheduler, collaborative development
    and MPP supported functions