The example is not ideal for showcasing a graph analytics database because they could have used a traditional relational database to answer the same query, Which of my contacts work at Google?
Hi, I work at Kuzu and can offer my thoughts on this.
You're making a fair observation here and it's true for any high level query language - SQL and Cypher and interchangeable unless the queries are recursive, in which case Cypher's graph syntax (e.g., the Kleene star * or shortest paths) has several advantages. One could make the argument that Cypher is easier for LLMs to generate because the joins are less verbose (you simply express the join as a query pattern). This post is not necessarily about graph analytics. It's about demonstrating that it's very simple to develop a relatively complex application using LLMs and a database fully in-browser, which can potentially open up new use cases. I'm sure many people will come up with other creative ways putting these fully in-browser technologies, both graph-specific, and not, e.g., using vector search-based retrieval. In fact, there are already some of our users doing this right now.
Your concern makes sense, but in the demo we show, all your private data AND the graph database AND the LLM (basically, everything) is confined to your client session in the browser, and no data actually ever leaves your machine. That's the whole point of Wasm!
The graph that you build is more for your own exploration and not for sharing with the outside world.
Still, using non-personal example would mean the user wouldn't have to consider whether to trust you on that point (or do the analysis), and would make the technology demo friction-free.
imo, privacy shouldn't be the driver but the kicker, because it's so inflammatory.
We wont be seeing any ai examples that actually are anywhere near useful until we rewrite all serialization/de serialization into "natural language" as well as create layers upon layers of loops of frameworks with simulations and test cases around this nonsense
