Developer vs. production mode

Please refer to the architecture page for a detailed description of the superduperdb architecture.

There are several important services in a superduperdb setup which may be run in-process, or in their own micro-services and containers:

• jupyter notebook/ client
• change-data-capture (CDC) service
• compute
  • scheduler
  • workers
• vector-searcher service
• REST-ful server service

Development mode

With the default settings of superduperdb, all of these items run in a single process. This is great for:

• Debugging
• Prototyping
• Experimentation
• Exploration
• Querying superduperdb

Production

There are several gradations of a more productionized deployment. In the most distributed case we have:

• A jupyter environment running in its own process
• A distributed Ray cluster, with scheduler and workers configured to work with superduperdb
• A change-data-capture service
• A vector-search service, which finds similar vectors, given an input vector
• A REST server

In the remainder of this section we describe the use of each of these services