pyodbc VS jina

Python can script and view this via pyodbc... https://github.com/mkleehammer/pyodbc/wiki

I am not 100% sure you call stored procedure correctly. in the examples they declare @out parameter for the procedures with output.

pyodbc has the odb2 part figured out. This could be useful instead of reinventing the wheel. The rest I can't think of anything that has been done. Sounds like an interesting project.

From its documentation it looks like pyodbc conforms to the DB API, so you can probably use named parameters by passing a dictionary to execute(), as described here.

~ $ pip show pyodbc Name: pyodbc Version: 4.0.34 Summary: DB API Module for ODBC Home-page: https://github.com/mkleehammer/pyodbc Author: Author-email: License: MIT Location: /data/data/com.termux/files/usr/lib/python3.10/site-packages Requires: Required-by:

I am trying to migrate data from our Enterprise Data Warehouse to one of our own reporting databases via ODBC and Python scripts. The python scripts import pyodbc to handle the database connections and execute SQL queries. A system DSN is defined on our ETL server for each database involved in the process.

See the docs.

Jina mainly because of their use of neural networks and AI.

Jina - It’s an open-source project where you can build search engines. Well maybe not no code but it claims that you only need a few lines of code for creating projects. The project supports semantic, text, image, audio, and video search. What I’m also interested in is with their neural search and generative AI. I’m also interested in the amount of github repo that they have. I have this on my radar since this is also something I was interested in.

Do you guys have any ideas how we can match images on our database? We’re working on a project that about matching images on our database. We were trying to use SIFT and some other similar methods, but for some reason, nothing doesn’t seem to be working that well. Does anyone have any suggestions for the most effective way to do this? Maybe some open-source solutions like HuggingFace or Jina AI? We just want to make sure our image matching is correct and that part’s been a bit of a struggle on our part.

The tech lets you find 3D models without sifting through tons of text - An information retrieval framework does the heavy lifting and compares models to each other, no descriptions or keywords needed.

Jina AI -They offer a neural search solution that can help build smarter, more efficient search engines. They also have a list of cool github repos that you can check out. Similar to Vertex AI, they have image classification tools, NLPs, fine tuners etc.

Well, it's not exactly a new feature, but we've been working on early support for DocArray v2 in Jina.

Jina let’s you serve all of your models through the same Gateway while deploying them as individual microservices. You can also tie your models together in a pipeline if needed. Also some nice ML focussed features such as dynamic batching.