Data Acceleration Architecture

Access to legacy/mainframe systems is still often an obstacle for corporations. Making the information stored in these systems available to create novel user experiences, more efficient search capabilities and advanced visualisations, all with response times of milliseconds, are the challenges that Sngular is addressing with this solution.
Sngular Data Acceleration Architecture is a distributed platform for managing and propagating data hosted on any system in real time. This data repository provides a layer of services for digital channels and information tools through a series of pipelines that retrieve and update data.
Elastic infrastructure
Combined with containerised deployments and cloud environments, our architecture provides an elastic infrastructure that can respond to spikes in interface consumption without significant economic impacts on data access, a recurring problem when accessing a mainframe.
The benefits
Support for all major search models
The engine allows searching transactions based on open text fields, by amounts, by concepts, categories, and any combination. These search capabilities apply to the entire transaction history because they can be extended to all datasets.
Continuity of operations
In case of mainframe maintenance or mainframe downtime, the platform will allow end-users to at least access the information and will work in read-only mode. Operations persisting data modifications will not be possible, but the system will be accessible.
Independence of deployment models
The use of containers allows the platform to be deployed in the infrastructure model chosen by the customer.
Near real-time updates
The use of data streaming techniques means that the information remains updated, if not in real-time, then in near real-time (NRT).
Cost savings
Reduced consumption of reading operations against the host, making it more economically efficient.
Prepared for testing automation
Integration, and continuous deployment circuits, which accelerate development cycles.