Graph Database
topic on 3 shows · 10 statements across 9 episodes
Latent Space 
the MAD Podcast 
20VC
10 statements about Graph Database, every show
Bergum: Building knowledge graphs is the bottleneck in Graph RAG, not databases
“The core issue issue is actually to build the knowledge graph, right? The entities, the relationships. So if you say graph, graph, You know, databases or graph rag is going to kill vector rag and all that discussion. I think the first issue is to actually buil…”
Swyx: Most ML practitioners consider knowledge graphs a 'dirty word'
“Most ML practitioners would say that knowledge graph is kind of like a dirty word the graph database. People get graph religion, everything's a graph, and then they go really hard into it, and then they get a graph that is too complex to navigate.”
Hitchcock: Dedicated in-memory graph databases will always outpace multi-model engines
“If you're dealing with graph data that all sits inside memory and it's being stored in a graph data structure, then that's always going to be quicker on a graph database that is sitting on a single node.”
Yegge: PostgreSQL matches dedicated graph databases on most graph workloads
“There was some joint study between IBM and some other That basically showed that Postgres was performing as well as most of the graph databases for most graph workloads.”
Eifrem: Detecting normal-looking fraud rings requires graph databases
“What it won't capture is that what if you have a number of transactions that are all within this band of what's normal, but they're connected in fraudulent ways, like a fraud way. Like the only way you can find that is if you can operate and connect the data, …”
Eifrem: Graph databases could become a $20B to $40B market
“Databases is the biggest market in all enterprise software. It'll soon be a hundred billion dollar market. I think graph databases can be a significant chunk of that, 20, 30, forty billion dollar, right?”
White-Sullivan: Graph databases represent relationships between thoughts better than SQL
“We're so bullish on graph databases, is that they're a better representation for the relationship between thoughts, the relationship between projects, the relationship between people, and yeah, most of the tools that we have out there are based on the SQL data…”
Oudghiri: Graph databases are not yet sufficiently mature for enterprise outputs
“Graph databases are not quite where they are yet”
Maida: Graph databases excel at relationships but struggle with metadata and counts
“While the graph databases are really efficient and really good at storing the relationships between the various entities, they are not as good at doing things like storing additional metadata or quickly retrieving counts and the like.”
Eifrem: Graph databases were the fastest-growing database category for two years
“Graph databases, whilst being one of the smaller cousins of the former NoSQL phenomena, right has actually been the fastest growing category inside of all of big data, all of databases for the vast majority of the past two years.”