Data Integration for Hadoop Etl and Hadoop Data Warehouse
Hadoop data integration can be completed faster with Diyotta. With Diyotta, organizations can generate immediate and long-term value from their new Hadoop investment.
Diyotta Works on All Hadoop Distributions
A certified solution, purpose-built for Big Data with fast implementation for quick returns on your hadoop investments. Transform Hadoop into a powerful hub.
A unified metadata-driven solution to manage data integration on the Hortonworks data platform and traditional data warehouses.Learn More
A unique design approach for defining data transformation and integration processes. Utilize Hadoop by leveraging a seamless solution between Hive and Impala.Learn More
A unified architecture purpose-built for seamless big data integrations that leverage core components of the innovative MapR architecture including MapRFS and Spark.Learn More
With the in-memory technology from Spark and the scale-out capabilities from Hadoop, Diyotta delivers a high-performing Big Data integration solution on Splice Machine RDBMS.Learn More
Diyotta leverages GPFS and BigSQL – the core components in IBM BigInsights, to provide enterprise-class file management and Hadoop SQL processing.Learn More
Diyotta natively integrates with the Pivotal Big Data Suite on ODPi, utlizing Pivotal’s proven scale-out databases including: Pivotal Greenplum and Pivotal HDB.Learn More
Diyotta Makes Hadoop Gather Valuable Data Faster
Centrally manage all business rules and design data flows easily to maximize Hadoop investments. Watch the Sprint video to learn from their experiences.
- Maximize today’s technologies and future-proof architectures for maximum ROI
- Bring enterprise data standards to Big Data analytics and the cloud
- Remove unnecessary complexities of data integration
Data Ingestion for Hadoop
Organizations need a solution to ingest data from various legacy, operational and new source systems which could be structured, semi-structured or unstructured. Diyotta’s purpose-built solution for Hadoop helps organizations provide a robust data integration framework for Big Data architectures. With Diyotta, you can easily scale out data processing on-premises, in the cloud or hybrid environments. In addition, data can be rapidly ingested using wizards provided by Diyotta for users with limited or no knowledge of Hadoop.
Data Transformation and Processing on Hadoop
Users can accelerate the implementation of data logic within Hadoop and deliver immediate business value. Diyotta provides native functional libraries to support data transformation in Hadoop using Hive, Impala, Spark and many others. Users can perform complex processing by using Diyotta that dyanmically generates Hadoop native code.
Data Provisioning from Hadoop
In order to make important business decisions, people need data. Diyotta provisions data from Hadoop to downstream applications or users. Diyotta includes a graphical user interface with intuitive navigation for designing data flows and helps make data available quickly and efficiently.
Data Integration is 70% of Every Big Data Project
A large portion of Big Data projects are delayed through the use of traditional data integration approaches. With Diyotta's automated code generation, organizations can reduce the implementation and complexity of most Big Data projects. Historical results show that 70% of every project involves movement and integration of data and Diyotta offers a single solution to orchestrate the implementation and configuration on Hadoop, MPP and NoSQL platforms.