Diyotta at a Glance
Diyotta accelerates time to value of enterprise data assets by fully leveraging the power of MapR through a high-performing and intuitive solution - the Diyotta Data Integration Suite.
Enterprises Today Require Big Data Integration Tools
The digital and social revolution demands enterprises collect, transform, store and
analyze massive volumes of data. There are multiple factors adding to the overall
data explosion including new business processes, new data sources, increased
regulations and increased activity, all of which lead to significant generation of
multiple terabytes of data. Due to these factors, the scale of data that companies
need to manage today overwhelms traditional systems. Firms must embrace new
technologies to unlock the power of their data to turn it into actionable insights.
Data integration in the big data world can be very complex. When using the MapR Distribution including Apache™ Hadoop© as an integral component of your enterprise architecture, there is still the need to work with existing systems such as MPP data warehouses and traditional data repositories. Moving data from these sources to MapR needs to be efficient, and leveraging the processing capabilities of Hadoop to transform data is critical. With scaling difficulties and not having a right-fit architecture, traditional data integration tools become a bottleneck in your big data solution.
MapR and Diyotta Extend Your Modern Data Architecture
MapR provides a powerful, efficient, and enterprise-ready Hadoop distribution to store, process, and analyze all your data to help you gain the competitive advantage you seek. By adding the Diyotta Data Integration (DI) Suite, you get a technology specifically designed to solve big data integration challenges. Diyotta loads and transforms data by leveraging the processing power of Hadoop through a complete push-down approach. The DI Suite has no need for additional computing resources or intermediate data transformation servers. From source to target and data to information, Diyotta intelligently orchestrates the complete solution for a modern data architecture.
Architectural Optimization at the Core
High Performance and CostEffectiveness for Your Big Data Platform
Unlike conventional data integrations solutions which have been cobbled together
with multiple disparate components to facilitate enterprise-wide data integration -
particularly with the advent of Hadoop, Diyotta is based on an innovative unified
architecture purpose-built for seamless big data integration.
Designed for large-scale distributed computing platforms like the MapR Distribution, Diyotta not only delivers the highest level of performance possible for the execution of data transformation and validation processes, but also is the most cost-effective solution available. MapR provides a significant performance advantage over other distributions for Hadoop due to its architectural optimizations at the core level. A combined MapR and Diyotta solution offers the highest performance big data deployment based on Apache Hadoop. The efficiency of the solution leads to the cost-effectiveness you need to manage the expenses of a big data environment.
By eliminating the intermediate ETL infrastructure, essentially getting out of the way of your data, Diyotta employs a frictionless approach to data movement across the enterprise to move data at wire speed. This significantly reduces data latency, and reduces the time required to take data from source systems, perform the necessary transformations, and get the data to its final form from hours to minutes.
Diyotta helps you maximize the benefits of the data lake architecture with MapR through our revolutionary architecture for big data integration. Diyotta enables companies of all sizes to accelerate time to value of their data assets for BI reporting and analytics by fully leveraging the power of MPP data warehouse appliances and Hadoop through a feature-rich, intuitive and high-performing big data solution. Diyotta provides a fully integrated, modular platform to optimize and automate data integration through a unique frictionless approach to data movement, simply extracting, compressing and moving source data directly to your warehouse or Hadoop systems, leveraging the target platform as the transformation engine. For more information, please visit us at www.diyotta.com.
Diyotta flawlessly manages data extraction and transfer with unmatched speed, stability, and ease. Diyotta loads and transforms data by leveraging the processing power of Hadoop through a complete push-down approach, providing a purpose-built architecture for data movement and transformations on Hadoop.
MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified distribution for Hadoop. MapR is used by more than 500 customers across financial services, government, healthcare, manufacturing, media, retail and telecommunications as well as by leading Global 2000 and Web 2.0 companies. Investors include Google Capital, Lightspeed Venture Partners, Mayfield Fund, NEA, Qualcomm Ventures and Redpoint Ventures.
MapR for ETL/ELT Offloading
With Diyotta’s unique architecture, porting existing ETL/ELT datacentric processes to Hadoop via a combination of programming and HiveQL instructions is extremely easy and highly optimized.
Extending Functionality for MapR
Diyotta isolates developers from creating scripts or programs for data extraction or transformations by providing a simple to use and intuitive GUI. This lets you leverage MapR as the data transformation engine.
Unified Solution with MapR in
Data Lake Architecture
Diyotta’s versatile capabilities that let you work with multiple platforms in a seamless manner provides a unified solution to manage all your big data integration of MapR with other repositories.
Purpose-Built for Big DataDiyotta provides a unified data
integration solution which supports
data lake architectures, ensuring
optimal performance for extraction,
loading, and transformations.
The features like compression, parallel extraction, multi-threaded loads, native functions support, and optimized SQL build based on the target platform guarantee full flexibility and optimization.
Diyotta uses a metadata driven approach which lets you leverage new technologies just by changing configuration parameters.
One unified big data platform for Hadoop, NoSQL, database, and streaming applications.
Proven Production Readiness
Get enterprise-grade reliability with MapR, including built-in high availability and disaster recovery capabilities, proven in production to meet stringent service-level agreements.
Consistent High Performance
Do more work with less hardware for lower TCO versus other distributions of Hadoop.