Retrospection and Learnings from Dgraph Labs
11–20 of 40 posts
Re: Retrospection and Learnings from Dgraph Labs
#12The biggest pain point for me was the query language schizophrenia: Incomplete support for GraphQL, or their custom Dgraph Query Language (DQL). As Manish said, they missed the GraphQL train. They really should have gone all in on GraphQL, and only GraphQL.
Re: Retrospection and Learnings from Dgraph Labs
#13I may be in the minority opinion here, but I think the biggest issue was the product constantly changed and tried to be too many things. The product-market fit seemed to be on be "The GraphQL" db. But they really just did all this other complex stuff and by the time they were going in that direction ran out of steam. I don't know Manish personally, but there seems to be a lot of negative sentiment about his managemen…
I wonder if this sentence has similar basis:
From the blog post: "Dgraph took a hit suddenly due to a critically wrong hire — which made us go from a “things are looking great” to “sorry, you’re out” within a week."
Re: Retrospection and Learnings from Dgraph Labs
#14Some observations as a team active here.
We're adjacent / complementary because we make graph db's (and regular SQL/databricks/etc.) more actionable via rich & scaled graph viz workflows (analyst-facing) + graph automl (automation-facing), so sometimes end up working alongside graph db co's at enterprise/gov/tech customers so not just a silo'd db. I think we only saw ~1 production user of dgraph though, so entirely based on their competitors:
* Graph DB TAM: Neo4j revenue is probably around $200M/yr now, and probably another $100-200M across the other graph db vendors. (Market analysts say the graph db market today is $1B+ but seems rosy.) Importantly, because of analyst + AI use case growth in areas like recommendations, anti-fraud, cyber, etc., and streamlining of infra via cloud/docker/etc, everyone good is growing quite well, and I expect good YoY growth for everyone for at least 3 more years. The AI market likely a much bigger leap for graph, tho less clear for these graph db and especially cpu ones.
* GraphQL TAM: Agreed. But may be a bigger culture shock for a pivot. Not ready for Series B levels of expections. leading to...
* Revenue: Super risky, lacking big & growing revenue, to assume a Series A, and then a Series B (!), unless you have a special trick like having ties to the chinese government or being a successful serial founder people just trust.
* ... Tip for people looking at jobs: ask revenue / spending ratio + how many years in the bank when not profitable. If a b2b team can't make revenue work after $xM raised, they're on the path for stressful grinding, dilutive bridges & shutdown. VC treadmill grows expectations, so coming in from behind is asking for PE to take over or an acquihire where only the founders win.
Re: Retrospection and Learnings from Dgraph Labs
#15I don't understand what this could mean? How can a single hire be so impactful and so quickly? I guess the team was small but even then I'd be very interested to know how that could happen!
Re: Retrospection and Learnings from Dgraph Labs
#16>Dgraph took a hit suddenly due to a critically wrong hire — which made us go from a “things are looking great” to “sorry, you’re out” within a week. I don't understand what this could mean? How can a single hire be so impactful and so quickly? I guess the team was small but even then I'd be very interested to know how that could happen!
Re: Retrospection and Learnings from Dgraph Labs
#17Re: Retrospection and Learnings from Dgraph Labs
#18I used Dgraph as the primary data store in a production app for over a year. I really enjoyed thinking of our model in terms of a graph, and finding creative ways to query what we needed. The biggest pain point for me was the query language schizophrenia: Incomplete support for GraphQL, or their custom Dgraph Query Language (DQL). As Manish said, they missed the GraphQL train. They really should have gone all in on G…
Re: Retrospection and Learnings from Dgraph Labs
#19I may be in the minority opinion here, but I think the biggest issue was the product constantly changed and tried to be too many things. The product-market fit seemed to be on be "The GraphQL" db. But they really just did all this other complex stuff and by the time they were going in that direction ran out of steam. I don't know Manish personally, but there seems to be a lot of negative sentiment about his managemen…
I think this is sort of obvious. Imagine fixing a bug in your own personal project, compare that to fixing a bug in someone else's project. You can probably see the error and guess what the bug is, accurately, if it's your project. With someone else's code you're going to have to reverse engineer the system first.