Production features in Superduper
Superduper was made with productionization in mind. These means several things:
Modifiable, configurable, flexible​
A production ready solution should not come up short, as soon as developers encounted a use-case or scenario outside of the norm, or the documented applications. In this respect, modifiablility, configurability and flexibility are key.
Superduper contains fully open-source (Apache 2.0, MIT, BSD 3-part) components for all aspects of the setup. This goes from the AI-models integrated, the databases and client libraries supported, as well as the cluster and compute management. This means that developers are never left hung out to dry with regard to taking action in altering and interrogating the source doe, as well as adding their own functionality.
In addition, Superduper may be used and configured in a wide variety of ways. It can be used "in-process", with computations blocking ("developer mode") and it can be operated in a cluster-like architecture, with compute, vector-search, change-data capture and a REST-ful server separated into separate services. This is ideal for teams of developers looking to productionize their AI-data setups.
Scalability​
A production ready solution should scale with the amount of traffic, data
and computation to the system. Superduper includes a ray integration
which allows developers to scale the compute as the amount of data and requests
to the system grod. Read more here.
In addition Superduper has the option to separate the vector-comparison and sorting component into a separate service, so this doesn't block or slow down the main program running.
Interoperability​
Due to the change-data-capture component, developers are not required to operate their database through Superduper. Third-party database clients, and even other programming languages other than Python may be used to add data to the database. Nonetheless, Superduper will still process this data.
In addition the REST API may be easily used to access Superduper from the web, or from other programming environments.
Live serving​
The REST API service may be used to access Superduper using pure JSON, plus references to saved/ uploaded binaries. This gives great flexibility to application developers looking to build on top of Superduper from Javascript etc..
SuperDuper protocol​
All Superduper components may be built using Python, or directly in a YAML/ JSON formalism usng the "superduper-protocol". This provides a convenient set of choices for AI engineers, infrastructure engineers and beyond to share and communicate their AI-data setups in Superduper