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MongoDB acquires Voyage AI

investors.mongodb.com

41–50 of 172 posts

Re: MongoDB acquires Voyage AI

#41

How does MongoDB still have that much available to spend? Everyone I know moved off it years ago.

Pretty sure they achieved fiscal nirvana by exploiting enterprise brain rot. You hook em, they accumulate tech debt for years, all their devs leave, now they can't move away & you can start increasing prices. Eventually the empty husk will topple over but that's still years away.

Unironically, this.

Re: MongoDB acquires Voyage AI

#42

How is MongoDB still a thing when there's already several ways to handle json in Postgres including Microsofts new documentdb extension: https://gist.github.com/cpursley/c8fb81fe8a7e5df038158bdfe0f... What am I missing? Are Mongo users simply front end folks who didn't have time to learn basic SQL or back end architecture?

We use their atlas offering. It’s a bit pricey but we are very happy with it. It’s got a bunch of stuff integrated - vectors, json (obviously), search and charting along with excellent support for drivers and very nice out of the box monitoring.

Now I could possible spend a bunch of time and do the same thing with open source dbs - but why? I have a small team and stuff to deliver. Atlas allows me to do it fast.

Re: MongoDB acquires Voyage AI

#44

How is MongoDB still a thing when there's already several ways to handle json in Postgres including Microsofts new documentdb extension: https://gist.github.com/cpursley/c8fb81fe8a7e5df038158bdfe0f... What am I missing? Are Mongo users simply front end folks who didn't have time to learn basic SQL or back end architecture?

If you can learn Mongo you can learn SQL and 'back end architecture' let's be honest the basics are hardly difficult no matter what tool you're using.

Just because Postgres is good doesn't mean other things can't also be good (and better for some use cases).

Re: MongoDB acquires Voyage AI

#45

How is MongoDB still a thing when there's already several ways to handle json in Postgres including Microsofts new documentdb extension: https://gist.github.com/cpursley/c8fb81fe8a7e5df038158bdfe0f... What am I missing? Are Mongo users simply front end folks who didn't have time to learn basic SQL or back end architecture?

Mongo is Firestore for entrprise

Re: MongoDB acquires Voyage AI

#46

How does MongoDB still have that much available to spend? Everyone I know moved off it years ago.

This may be a shock to many HN readers, but MongoDB's revenue has been growing quite fast in the last few years (from 400M in 2020 to 1.7B in 2024). They've been pushing Atlas pretty hard in the Enterprise world. Have no experience with it myself, but I've heard some decently positive things about it (ease of set up and maintenance, reliability).

Re: MongoDB acquires Voyage AI

#47

I rather them focus on performance. Last MongoDB is still slower than MongoDB 3.4. An almost 10-year old release. For both reads and writes.

Can you share more details about the conditions under which it is slow in recent versions? We moved from 3.x to 7 for our main database and after adding a few indexes we were missing we have seen at least an order of magnitude speed up.

Re: MongoDB acquires Voyage AI

#48
post #43

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...

Re: MongoDB acquires Voyage AI

#49
I understand the criticisms, but in my experience, MongoDB has come a long way. Many of the earlier issues people mention have been addressed. Features like sharding, built-in replication, and flexible schemas have made scaling large datasets much smoother for me. It’s not perfect, but it’s a solid choice.

Re: MongoDB acquires Voyage AI

#50
post #20

what's the calculus here? if i'm a developer choosing a low-level primitive such as a database, i'm likely quite opinionated on which models i use.

If I had to guess they might see embedding models become small and optimised enough to the point that they can pull them into the DB layer as a feature instead of being something devs need to actively think about and build into their app.

Or it could just be an expansion to their cloud offering. In a lot of cases embedding models just need to be 'good enough' and cheap and/or convenient is a winning GTM approach.

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