The platform uses open-source data technology within a modern, serverless cloud-native design. In case that may be too many hyphenated technology terms for some, lets break that down some more.

The open-source data technology part is what some journalists might refer to as “big data” technologies. Given the original designers, ongoing development contributions and internet-scale usage patterns of technologies such as Apache HBase and Apache Kafka, the Datasynthesis Platform is built using technology components that are proven and reliable.

These data technologies are used within our platforms serverless, cloud-native design. A serverless architecture is a way to run and build applications without having to manage infrastructure, and is closely aligned concept of cloud-native design. Many vendors claim that their tools and applications are available as cloud services, but more accurately such vendors should describe their products as “cloud-based” since the underlying architecture has not been changed significantly, and as such are still limited by their on-premise, typically client-server, design. In contrast, a cloud-native design has been built only for the cloud, to take full advantages of its effectively infinite processing and storage capabilities.

Putting the technical descriptions to one side, then in summary all this means that the Datasynthesis Platform automatically scales to perform well regardless of processing needs, storage requirements and the number of simultaneous users. And with scalability removed as a constraint, its possible to deliver services to all users that are more complete in scope, more timely and less complex to use.