Show HN: Chroma Cloud – serverless search database for AI

Show HN: Chroma Cloud – serverless search database for AI(trychroma.com)

93 points by jeffchuber 272 days ago | 40 comments

Hey HN - I’m Jeff, co-founder of Chroma.

In December of 2022, I was scrolling Twitter in the wee-hours of the morning holding my then-newborn daughter. ChatGPT had launched, and we were all figuring out what this technology was and how to make it useful. Developers were using retrieval to bring their data to the models - and so I DM’d every person who had tweeted about “embeddings” in the entire month of December. (it was only 120 people!) I saw then how AI was going to need to search to all the world’s information to build useful and reliable applications.

Anton Troynikov and I started Chroma with the beliefs that:

1. AI-based systems were way too difficult to productionize

2. Latent space was incredibly important to improving AI-based systems (no one understood this at the time)

On Valentines Day 2023, we launched first version of Chroma and it immediately took off. Chroma made retrieval just work. Chroma is now a large open-source project with 21k+ stars and 5M monthly downloads, used at companies like Apple, Amazon, Salesforce, and Microsoft.

Today we’re excited to launch Chroma Cloud - our fully-managed offering backed by an Apache 2.0 serverless database called Chroma Distributed. Chroma Distributed is written in Rust and uses object-storage for extreme scalability and reliability. Chroma Cloud is fast and cheap. Leading AI companies such as Factory, Weights & Biases, Propel, and Foam already use Chroma Cloud in production to power their agents. It brings the “it just works” developer experience developers have come to know Chroma for - to the Cloud.

Try it out and let me know what you think!

— Jeff

wferrell 271 days ago |

Happy paying user of Chroma Cloud here. Congratulations Jeff, Hammad and team!

We were lucky to get early access and have saved a bundle.

BrandiATMuhkuh 271 days ago |

Chroma looks cool. Congratulations on the Cloud version.

For my client I've "built" a similar setup with Supabase + pgVector and I give the AI direct SQL access.

Here is the hard part: Just last week did I index 1.2 million documents for one project of one customer. They have pdfs with 1600 pages or PPTX files of >4GB. Plus lots of 3D/2D architecture drawings in proprietary formats.

The difficulty I see is - getting the data in ETL. This takes days and is fragile - keep RBAC - Supabase/pgVector needs lots of resources when adding new rows to the index -> wish the resources scale up/down automatically. Instead of having to monitor and switch to the next plan.

How could chroma help me here?

jeffchuber 271 days ago | |

> Supabase/pgVector needs lots of resources when adding new rows to the index -> wish the resources scale up/down automatically. Instead of having to monitor and switch to the next plan.

Many ways potentially - but one way is Chroma makes all this pain go away.

We're also working on some ingestion tooling that will make it so you don't have to scale, manage or run those pipelines.

BrandiATMuhkuh 271 days ago | | |

I'll for sure take a deeper look. Ingestion has been by far the biggest pain and least fun. Those infra parts hold us back from the cool things -> building agents/search

Tsarp 271 days ago |

Im using LanceDB (and pretty happy with it so far). I am looking at the chroma docs and have a few questions

1. I see the core is OSS, any chance of it being pushed up on crates.io(i see you already have a placeholder)

2. Is it embeddable or only as a Axum server?

Do you see all providers converging on similar alpha i.e cheap object storage, nvme drives,ssd cache to solve this?

Cheers and congrats on the launch

jeffchuber 271 days ago | |

Hey there

Chroma is fully OSS - embedded, single-node and distributed (data and control plane). afaik lance distributed is not OSS.

We do have plans to release the crate (enabling embedded chroma in rust) - but haven't gotten around to it yet. Hopefully soon!

> Do you see all providers converging on similar alpha i.e cheap object storage, nvme drives,ssd cache to solve this?

It's not only a new pattern in search workloads, but it's happening in streaming, KV, OLTP, OLAP, etc. Yea - it's the future.

srameshc 271 days ago |

I appreciate the straightforward pricing calculator and the pricing seems very reasonable.

jeffchuber 271 days ago | |

thank you!

curl-up 271 days ago |

Can Chroma handle combined structured+vector search? E.g. filtering by `category=X and value>Y` then finding top N matches by vec similarity?

HammadB 271 days ago | |

Yes! It can - https://docs.trychroma.com/docs/querying-collections/metadat...

tbird24 271 days ago |

I run a fractional jobs site. Lots of non-technical customers are interested in ai. What problem does Chroma solve for these non-technical users?

philip1209 271 days ago | |

High-level, Chroma lets you incorporate your own data into AI. That can be business data, like your help docs, or customer data, such as private documents.

I think there's a misconception among many non-technical people that they should "fine tune" models - to make an LLM sound like their brand or know their internal data. But, the best practice today is "context engineering" - to use a commodity LLM, and add propriety information into the prompt.

The hard part of context engineering is knowing which data to incorporate. For example, all help docs in every context creates context rot [1] that hurts accuracy, so you need a way to find which information to put in which context. The solution is essentially an internal search engine, which is Chroma.

Chroma gives AI multiple ways to search, and you can either hard-code which one works best for you - or let an agent write its own queries to conduct research by itself. Vector search is a generation ahead of old search infrastructure, and is useful for relatedness queries - like "help docs about billing". Full-text search is useful for proper nouns, like "Next.js". Regex search is useful for code and laws. Metadata search is more nuanced, but becomes really important in document search (e.g., PDFs). Chroma lets you run all of these search methods against private data, and you can use it to even include citations in results.

So, the high-level answer is: Chroma enables you to incorporate your business or customer data into AI.

[1] https://research.trychroma.com/context-rot

4ndrewl 271 days ago | |

Not sure why this is voted down. The site doesn't really explain what problems of mine it'll solve (if any). I just came away thinking "oh, it's a thing. might have been a useful thing, who knows"

"Sell the sizzle, not the steak" is a real thing for a reason.

HammadB 271 days ago | | |

That is helpful feedback, thank you. We'll address this.

jeffchuber 271 days ago | |

your customers might have heard of RAG (retrieval augmented generation) before. chroma powers the “R” in RAG. It enables language models to dynamically pull in information to help them answer questions and solve tasks.

tristanho 271 days ago |

Doesn't this does seem like a bit of an... exact rip off of turbopuffer?

Down to the style of the webpages and the details of the pricing?

Here's the pricing calculator, for example:

https://share.cleanshot.com/JddPvNj3 https://share.cleanshot.com/9zqx5ypp

As a happy turbopuffer user, not sure why I'd want to use Chroma.

taikon 271 days ago |

I still remember when the website said Chroma Cloud was coming end of 2023. What took so long?

jeffchuber 271 days ago | |

very fair!

cloud has been in private beta for a year now.

we chose to not release it to the public until we were extremely confident in the system and its characteristics.

databases are a serious business. developers trust us with their mission critical data.

thatwasunusual 271 days ago |

I haven't heard of Chroma before (sorry about that), but how does it compare to Weaviate?

jeffchuber 271 days ago | |

no worries!

Chroma and Weaviate are both popular OSS projects, 21k and 14k stars respectively.

Weaviate has some features that Chroma does not (yet) - notably vector quantization. Weaviate is a single-node DB that can be run in cluster mode.

Chroma focuses on reliability and operational simplicity. The fully distributed architecture means there are no knobs to tune or config to set.

There's no right tool for everyone. Try both!

skeptrune 271 days ago |

I'm excited to see Chroma be fully available! They're already differentiated from Turbopuffer/S3-vector with regex support and I think they will only get more so with sparse vector support and some kind of API surface which enables LTR.

codekisser 271 days ago |

what place do vector-native databases have in 2025? I feel using pgvector or redisearch works well and most setups will probably be using postgres or redis anyway.

maz1b 271 days ago |

Best of luck. Do you guys have anything for startups?

philip1209 271 days ago | |

Philip here from the Chroma team.

I see your email in your profile, so I'll reach out.

We work closely with any startup that wants help, ranging from whiteboarding architectures to a shared slack channel.

acohn24 271 days ago |

we want to create vector search for people — what's the best way to use Chroma Cloud for that?

jeffchuber 271 days ago | |

can you tell me more about your use case?

poopiokaka 271 days ago |

Why does it say open source but then try to charge me money

philip1209 271 days ago | |

Chroma's open-source under an Apache 2.0 License: https://github.com/chroma-core/chroma

Single-node Chroma is very easy to self-host for free: https://docs.trychroma.com/guides/deploy/docker

tomrod 271 days ago | |

Typical FOSS model to offer a super useful core then charge for ancillary services and consulting to pay for development of the core.

It's a great model for people who want to have grasp beyond the typical software reach.

malcolmgreaves 271 days ago | |

“Free as in freedom, not as in beer.”

https://en.m.wikipedia.org/wiki/Gratis_versus_libre

didip 271 days ago |

What about comparison with Qdrant?

jeffchuber 271 days ago | |

Qdrant team is also smart!

The main reason we have seen people switch from Qdrant to Chroma is for operational simplicity and reliability. With Qdrant you have to size nodes, manage sharding, be oncall, etc - with Chroma there is literally 0 config or operational pain. Search, that just works!

Efqan 271 days ago |

Hack