Snowflake's AI "Intelligence": Or, How to Sell You the Same Dream, Again
So, Snowflake's at it again, huh? Unveiling their "Snowflake Intelligence" platform. Sounds impressive, right? Like they've cracked the code to AI and are ready to bestow its glorious wisdom upon us mere mortals. Except...give me a break.
It's the same song and dance we've been hearing for years from every enterprise software vendor out there. From Snowflake to Databricks, they're all peddling the same snake oil: "Our AI will solve all your problems! Just plug it in, and watch the magic happen!"
They're all chasing that AI-powered agent dream. Databricks fires back at Snowflake with SQL-based AI document parsing, and Snowflake is building new intelligence that goes beyond RAG to query and aggregate thousands of documents at once. Okay, so what? It’s like watching toddlers fight over a shiny toy, except this toy costs millions and rarely works as advertised.
And let's be real, the core problem ain't the tech. It's the data. As the article points out, most organizations "can't answer basic analytical questions about their document repositories." That's not an AI problem; that's a garbage-in, garbage-out problem. You can't expect AI to magically conjure insights from a disorganized mess of data.
Snowflake is trying to move beyond Retrieval Augmented Generation (RAG) systems, which they claim are too limited for complex analytical queries. Jeff Hollan from Snowflake even uses the "librarian" analogy, saying RAG is like a librarian who can only point you to the page where the answer exists. Okay, fair enough. But their solution, "Agentic Document Analytics," sounds suspiciously like...more AI hype.
They claim it can analyze thousands of documents simultaneously and answer complex questions like "Show me a count of weekly mentions by product area in my customer support tickets for the last six months." Great. But what if those support tickets are filled with typos, sarcasm, and customer rage? Will the AI be able to decipher that? Will it understand the nuances of human language and emotion? I doubt it.
And offcourse, they’re touting that this will allow normal business users to get access to insights without a data scientist. Anyone who believes that has never worked in a real business.
Here's what's really going on: Snowflake wants to unify structured and unstructured data analysis within its platform. They want to be the one-stop shop for all your data needs. It's about vendor lock-in, plain and simple.
Speaking of lock-in, they’re open-sourcing their PostgreSQL extensions, pg_lake, to try and woo PostgreSQL developers. Snowflake claims this will allow developers to "read and write directly to Apache Iceberg tables from PostgreSQL, thereby cutting out the need to extract and move data." Sounds convenient, I guess. But I can't shake the feeling that it's just another way to get people hooked on the Snowflake ecosystem.
Christian Kleinerman, Snowflake's EVP of product, says this will allow developers to "turn the database into an interface to manage an open lakehouse." Oh, really? An "open" lakehouse controlled by Snowflake? Give me a break! That's like saying a prison is "open" because it has a revolving door...for the guards.
Robert Kramer from Moor Insights & Strategy thinks this is a smart move, saying it "lowers the barrier for PostgreSQL teams to gradually adopt Snowflake for high-value analytics and automation." Maybe. Or maybe it's just a way for Snowflake to squeeze more money out of unsuspecting customers.
The article ends with Kleinerman urging everyone to "start building now" with AI. But wait, are we really ready? Are we sure we understand the implications of handing over our data to these AI overlords? Are we even asking the right questions?
Then again, maybe I'm the crazy one here. Maybe Snowflake really has cracked the code. Maybe AI really will solve all our problems. But I doubt it.
