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MQL – Client and server to query your db in natural language

59 pointsby akashkahlonabout 1 year ago

9 comments

brudgersabout 1 year ago
My 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.<p>I think that&#x27;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&#x27;t.<p>Furthermore there&#x27;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.
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kshitijbabout 1 year ago
For the majority of people from non-tech business functions, the ability to ask for insights from data is liberating. Tools like this can unlock their potential to make more informed decisions. Imagine a store manager of a hyperlocal grocery startup managing a dark store. What if they could ask questions like &quot;What is the fulfilment rate of a certain SKU between 12-3 pm in their store for the past 7 days?&quot;
mritchie712about 1 year ago
text-to-sql is a dead end. There&#x27;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&#x27;t use foreign keys, so you don&#x27;t even know the joins.<p>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&#x27;t answer them, they&#x27;ll ask you more questions. The conversation would go something like:<p>you: what is our churn rate by channel?<p>new analyst: where do we store &quot;channel&quot;? what do we use to process payments? where is that data stored? do we include discounts in MRR &#x2F; churn? etc.<p>If a human can&#x27;t do it, an LLM can&#x27;t either. An LLM isn&#x27;t able to write the SQL from scratch get the right answers without a ton of additional context. We&#x27;re working on an approach using a semantic layer at <a href="https:&#x2F;&#x2F;www.definite.app&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.definite.app&#x2F;</a> if you&#x27;re interested in this sort of thing.
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dragon96about 1 year ago
Genuine question: does anyone here actually want to query their database with natural language?
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zainhodaabout 1 year ago
Nice job getting something released! How does this compare to the other similar open source solutions like Vanna AI and DataHerald?
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Log_out_about 1 year ago
That &quot;natural language&quot; will magic and away complexity mindset has done so much damage.
jhoechtlabout 1 year ago
&gt; As of the current version, MQL is designed to work exclusively with PostgreSQL
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kelvinjpsabout 1 year ago
isn&#x27;t SQL already a way to query your DP with natural language?
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roydivisionabout 1 year ago
Or one could, you know, learn SQL.
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