Legacy data integration solutions were based on an Extract, Transform, and Load (ETL) model. These models were effective in an environment where data volumes were limited, data flowed in a more linear fashion, and all data resided on-premises. Given the twenty-plus years since the development of traditional ETL solutions, the data landscape has changed dramatically. Data volumes have sky rocketed and are increasing by the minute. Data has become much more complex and is no longer flowing in a linear fashion. It is coming and going in many formats and in all directions. Data no longer resides solely on-premises. It now resides on-prem, in both private and public clouds, and in multi-cloud environments. Traditional ETL solutions are not equipped for the scalability and portability required to manage the massive volumes and complexities of modern data.
Diyotta is an enterprise-class data integration solution that enables organizations to quickly and efficiently access data from diverse sources, regardless of whether the data resides on-prem or in the cloud. Unlike traditional ETL tools that utilize a proprietary processing engine to transform the data prior to loading it into the target, Diyotta delivers true pushdown to the processing engine, exposing native functions, code generation, and optimization at the design phase. By doing so, Diyotta removes the bottleneck typically experienced with traditional ETL solutions and takes advantage of the power of the chosen processing/compute platform.
In addition to pushing the processing down to the compute engine, Diyotta's unique modular architecture allows for increased volumes and scalability across multiple platforms, whether those platforms are cloud based or on-prem. Diyotta’s simple to use drag and drop user interface and modular approach streamlines the data integration development process and dramatically improves time to value.