Low-code framework to create, debug, and deploy data services in minutes
Assign roles, permissions and tokens to consuming applications
Rapidly compose complex logic and flow with a visual orchestration tool
The data services architectural style is a modern approach to developing an enterprise application as a suite of small services. These services are individually governed and independently deployable.
A data service typically interacts with other data services to do, what would traditionally be done, by one large, monolithic application.
Ultimately, the goal of a data services is to deliver quality software, quicker. Breaking down large applications into small data services is just the beginning.
Data services need to be quickly developed, orchestrated, debugged, and well-managed. That’s where data products come in.
The data structures that fed old monolithic applications were simply not designed for a data service architecture.
A data product approach delivers a complete dataset for a specific business entity (such as a customer, device, or invoice), where each dataset is managed in its own, secured Micro-Database™.
These Micro-Databases are accessible via secure data services, which data engineers can quickly generate, in support of operational and analytical workloads.
Data Product Platform generates data services automatically, maximizing efficiency, keeping data fresh, and delivering sub-second query response times.
Data Product Platform includes a comprehensive low-code/no-code framework for developers to rapidly create, orchestrate, debug, govern, and deploy data services.
Using a point-and-click graphical builder, developers generate web services and can optionally extend them using Java source code.
Developers can graphically orchestrate data services, and package the orchestrated data services as a composite data service. And a visual debugger is built in, enabling them to rapidly pinpoint and fix logic errors in, and between, the data services.
And full data service governance is enabled, with data masking via data masking tools, and access controls.
Although data services are intended to increase responsiveness and reduce costs, modifications to the underlying data sources and systems typically slow down and increase the costs of generating data services.
Most changes to the data sources and to the data products are handled automatically. Changes affecting the data product schema are applied, on the fly, to support a true CI/CD environment.
And learn more about automated data services
Get a live demo of the K2View platform to assess its fit for your use cases.
Experience the power and flexibility of the K2View platform with a 30-day trial.
Experience the power and flexibility of the K2View platform with a 30-day trial.
