131–140 of 172 posts
10x exit in a couple years, quite nice on the VC side! On the tech side ... no idea what Mongo's plan is ... their embedding model is not SOTA, does not even outperform the open ones out there, and reranking is a dead end in 2025. I think the value is on Voyage's team, their user base and having a vision that aligned with Mongo's. Congrats!
I have personally been incredibly impressed with the way MongoDB has "looked out" for my company over the past year. I'll try to be satisfactorily specific their with privacy in mind, so this may come out a bit fuzzy. Their technical teams, both overseas and US, have produced some of the most thorough, detailed recommendations I have ever seen and their communication/followup was excellent. I've run many designs and ideas by their team, out of habit at this point, and have always been pleased with the response. They remember who I am. All of this is really unusual for a company at my growth stage.
My use case requires full technical depth on text searching and vectorization; I use every aspect of Atlas Search that is available. A downside of building "bleeding edge" is that my tooling needs always seem to be just inches beyond what is available, so just about every release seems to have something that is "for me." It's hard to say if my feedback specifically has an impact on their roadmap - but they really do seem to build things I want. I think they reported ~50% better performance on bulkWrite() in the 8 release, but it was closer to 500% for my use case.
Speaking of, this acquisition is like providence for me, because I've shared my various solutions with them for synchronously vectorizing "stuff" for use with local LLMs. It's a reasonably hard technical problem without a lot of consensus on standards; I think a lot of people believe there are standards, yet any discussion will quickly devolve into something like the "postgres/mongo" conversations you see here (I won't be visiting that topic).
I strongly agree with the "this should be a database level feature" approach they are taking here; that's certainly how my brain wants to think about it and currently I have to do a lot of "glue"-ing to make it work the way I require.
I hope they win.
For context, I am a startup founder, an Atlas user, and not what anyone would call a "major account". I'm also in my early 30's, so I wasn't around for the whole "web scale" meme era of MongoDB. I have personally been incredibly impressed with the way MongoDB has "looked out" for my company over the past year. I'll try to be satisfactorily specific their with privacy in mind, so this may come out a bit fuzzy. Their t…
For context, I am a startup founder, an Atlas user, and not what anyone would call a "major account". I'm also in my early 30's, so I wasn't around for the whole "web scale" meme era of MongoDB. I have personally been incredibly impressed with the way MongoDB has "looked out" for my company over the past year. I'll try to be satisfactorily specific their with privacy in mind, so this may come out a bit fuzzy. Their t…
So basically you see this as helping to get working vector search in MongoDB? It sounds as if the attraction, then, is that it integrates easily with your existing Atlas usage. Or is there more?
Voyage AI basically builds embedding models for vector search
You don't hear the big AI providers talk about embeddings much, but I have to believe in the long run that companies building SOTA foundational LLMs are going to ultimately have the best embedding models. Unless you can get to a point where you can make these models small enough that basically sit in the DB layer of an application...
Earlier quoted context omitted.
Mongo is real distributed and scalable DB, while postgres is single server DB, so main consideration could be if you need to scale beyond single server.
sigh See https://jepsen.io/analyses for how MongoDB has a tradition of incorrect claims and losing your data. Distributed databases are not easy. Just saying "it is web scale" doesn't make it so.
1. That PgSQL also has issues in jepsen tests?
2. of any distributed DB which doesn't have jepsen issues?
3. It is configurable behavior for MongoDB: can it lose data and work fast, or work slower and do not lose data. There is no issues of unintentional data loss in most recent(5yo) jepsen report for MongoDB.
Earlier quoted context omitted.
sigh See https://jepsen.io/analyses for how MongoDB has a tradition of incorrect claims and losing your data. Distributed databases are not easy. Just saying "it is web scale" doesn't make it so.
Are you aware: 1. That PgSQL also has issues in jepsen tests? 2. of any distributed DB which doesn't have jepsen issues? 3. It is configurable behavior for MongoDB: can it lose data and work fast, or work slower and do not lose data. There is no issues of unintentional data loss in most recent(5yo) jepsen report for MongoDB.
Your second point seems to imply that everything has issues, so using MongoDB is fine. But there are various kinds of problems. Take a look at the report for RethinkDB, for example, and compare the issues found there to the MongoDB problems.
Earlier quoted context omitted.
Are you aware: 1. That PgSQL also has issues in jepsen tests? 2. of any distributed DB which doesn't have jepsen issues? 3. It is configurable behavior for MongoDB: can it lose data and work fast, or work slower and do not lose data. There is no issues of unintentional data loss in most recent(5yo) jepsen report for MongoDB.
Distributed databases are not easy. You can't simplify everything down to "has issues". Yes, I did read most Jepsen reports in detail, and struggled to understand everything. Your second point seems to imply that everything has issues, so using MongoDB is fine. But there are various kinds of problems. Take a look at the report for RethinkDB, for example, and compare the issues found there to the MongoDB problems.
RethinkDB doesn't support cross document transactions, problem solved lol
Genuine question: I appreciate the comments about MongoDB being much better than it was 10 years ago; but Postgres is also much better today than then as well. What situations is Mongo better than Postgres? Why choose Mongo in 2025?
In MongoDB the situation is different. You have to deal with the bare minimum of a database. But in return your data design has much higher horizontal scalability survivability.
In the initial phase of your startup, choose MongoDB. It's easier to start and evolve in earlier stages. And later on, if you feel the need and have resources to scale PostgreSQL, move your data there.