MQL – Client and server to query your db in natural language
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Re: MQL – Client and server to query your db in natural language
#2[deleted]
Re: MQL – Client and server to query your db in natural language
#3My experience with this kind of tool is that it is at least as hard to learn the tool as it is to learn the technology it abstracts over.
I think that's because thinking about the problem I am trying to solve is always the hardest part and I have to learn a syntax and semantics no matter what. And the syntax and semantics of SQL is mathematically linked to the mathematics of relational databases. Natural language isn't.
Furthermore there's decades of good technical documentation for SQL written by diverse authors for diverse levels of technical experience. Natural language projects are one off and writing documentation is usually a lower priority than making code go.
Re: MQL – Client and server to query your db in natural language
#4Or one could, you know, learn SQL.
Re: MQL – Client and server to query your db in natural language
#5> As of the current version, MQL is designed to work exclusively with PostgreSQL
Re: MQL – Client and server to query your db in natural language
#6Nice job getting something released! How does this compare to the other similar open source solutions like Vanna AI and DataHerald?
Re: MQL – Client and server to query your db in natural language
#7> As of the current version, MQL is designed to work exclusively with PostgreSQL
Yes, we are working on adding MySQL support as well, would you suggest any other integrations after or before mysql ? happy to learn.
Re: MQL – Client and server to query your db in natural language
#8text-to-sql is a dead end. There's no way for a model to correctly interpret the meaning of every column in a real world database using the `information_schema` alone. Most cloud warehouses (e.g. Snowflake) don't use foreign keys, so you don't even know the joins.
Imagine you hire a highly skilled data analyst (e.g. 9 out of 10 proficiency in SQL) and start asking them questions about your database. They won't answer them, they'll ask you more questions. The conversation would go something like:
you: what is our churn rate by channel?
new analyst: where do we store "channel"? what do we use to process payments? where is that data stored? do we include discounts in MRR / churn? etc.
If a human can't do it, an LLM can't either. An LLM isn't able to write the SQL from scratch get the right answers without a ton of additional context. We're working on an approach using a semantic layer at https://www.definite.app/ if you're interested in this sort of thing.
Re: MQL – Client and server to query your db in natural language
#9Or one could, you know, learn SQL.
:D
We have been working with many non-tech founders and business people who are genuinely interested in data but they cannot learn SQL, due to different constraints.
Re: MQL – Client and server to query your db in natural language
#10text-to-sql is a dead end. There's no way for a model to correctly interpret the meaning of every column in a real world database using the `information_schema` alone. Most cloud warehouses (e.g. Snowflake) don't use foreign keys, so you don't even know the joins. Imagine you hire a highly skilled data analyst (e.g. 9 out of 10 proficiency in SQL) and start asking them questions about your database. They won't answer…
> There's no way for a model to correctly interpret the meaning of every column in a real world database using the `information_schema` alone.
Why would text-to-sql be limited to information_schema alone? Human analysts would use additional documentation, why wouldn't an LLM-based text-to-sql system?