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Use cases

The landscape of computing has been changing rapidly in the last decade and will continue to do so for many years to come as the world recovers from the global pandemic accelerating digital transformation. An in-browser technology like SQL Frames will be helping create a new breed of analytic solutions leveraging modern compute methods. Below are just a few examples.

Architectures​

  1. Serverless analytics Old style infrastructure heavy analytics stacks are being replaced with serverless analytics architectures building data lakes and data warehouses on the cloud. This helps with cost savings while also improving the quality of service. SQL Frames operates within the browser and hence eliminates the need for a powerful server to process the data. It can act as an accelerator to provide milliseconds latency interactions to the already powerful serverless analytics stack.

  2. JAMSTACK analytics There is no reason for analytics interfaces to be stuck in the past. Make it easy for executives and senior management to consume data as simple as browsing a website. JAMSTACK together with SQL Frames makes working with analytics as simple as reading an article on the web by blending the data and narrative with simple markups.

Types of Data​

  1. Document-oriented Data NoSQL databases by definition do not have the same features as relational databases and that makes it challenging to provide ad-hoc analytics on them. SQL Frames allows storing data in NoSQL databases but also do client-side ad-hoc analysis using declarative SQL constructs.

  2. Remote Data There are times when the data is available from a remote system such as 3rd party REST APIs and the system may not be providing aggregated data or what it provides is limited. In such cases SQL Frames allows ad-hoc data analysis directly on the client by getting the remote data.

  3. Streaming data Some data such as stock market data and IT monitoring data are streamed directly to the dashboards in realtime. With SQL Frames these realtime data streams can be aggregated directly on the client avoiding latencies with server-side aggregation techniques.

  4. Public Data Some of the data in the public sector and charity organizations is open and accessible to everyone. While it is accessible to everyone, not everyone has the tools and knowledge of doing analysis to make their own decisions. This can be to decide on a proposition or to decide how their tax dollars are being put to use by the governing bodies. Being budget constrained it is difficult for these organizations to provide a cost-effective centralized data analysis solutions. SQL Frames can improve data transparency by making it reachable to the wider audience by moving the analysis to the client.

  5. Encrypted Data Some systems store data encrypted at rest and hence not possible to perform analytics on the server. Only a client with access to data can view the decrypted data. While solutions like Homomorphic Encryption allow certain computations on the server, SQL Frames allows all types of data manipulations by moving the computation to the client which has access to the decrypted data.

  6. Immutable data Immutability and decentralization has gained popularity with distributed ledger technologies such as blockchains. In this model, the client does not trust any single server and can itself verify the correctness of the data. With SQL Frames the data can further be aggregated and analyzed on the client bringing the same zero trust to aggregate data.

JAMStack

This is an example of JAMSTACK Analytics where this entire website is built using Docusaurus, a JAMSTACK static documentation site generator. All the examples in the documentation are live and blended with rest of the content.