đź”® SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.
For the built-in Leaf object in superduperdb, reduce the amount of information through special references
For example
Now
from superduperdb.components.datatype import pickle_serializer
from superduperdb import Document
Document({'id': 123, 'x': pickle_serializer('This is a test')}).encode()
Furthermore, we can even remove _builds:866cf8526595d3620d6045172fb16d1efefac4b1, because everything is built-in. As long as we have better protocol, it will eventually become xxxx.
{'id': 123,
'x': '&:protocol:{Artifact(datatype=&datatpye/pickle, blob=&:blob:866cf8526595d3620d6045172fb16d1efefac4b1)}',
'_blobs': {'866cf8526595d3620d6045172fb16d1efefac4b1': b'\x80\x04\x95\x12\x00\x00\x00\x00\x00\x00\x00\x8c\x0eThis is a test\x94.'}}
Ultimately, this protocol should have the following characteristics:
Improve information compression rate by utilizing the following mechanisms:
db.metadata, such as &:component:
db.artifact, such as &:blob: / &:file:
superduperdb’s codebase, such as &:new_type:
...
The encoded information should be readable and meaningful.
For the built-in Leaf object in superduperdb, reduce the amount of information through special references
For example
Now
We get
To
Furthermore, we can even remove
_builds:866cf8526595d3620d6045172fb16d1efefac4b1
, because everything is built-in. As long as we have better protocol, it will eventually become xxxx.Ultimately, this protocol should have the following characteristics:
Improve information compression rate by utilizing the following mechanisms:
The encoded information should be readable and meaningful.