Quoted post unavailable.
Which open source libraries is pinecone wrapping?
FAISS
Vector search just got up to 10x faster and vertically scalable
11–20 of 54 posts
Re: Vector search just got up to 10x faster and vertically scalable
#12Quoted post unavailable.
If you really think that's enough to build a real product, go for it. Even open-source companies (Elastic, Mongo, Scylla) have to build tons of infra around their core codebase in order to make it an actual cloud product.
Not that easy, the founder was a director at AWS. This is just devops/obfuscation on top of an open source library:
FAISS
Re: Vector search just got up to 10x faster and vertically scalable
#13Confused by their claim to be the 'first' vector database. These things have been around forever? For example FLANN (not a DB server, but example lib) is from 2009
Re: Vector search just got up to 10x faster and vertically scalable
#14Confused by their claim to be the 'first' vector database. These things have been around forever? For example FLANN (not a DB server, but example lib) is from 2009
I think the difference is in the layer of abstraction i.e. FLANN is just the underlying search functionality whereas vector databases are fully managed solutions. Even so, Weaviate came out in 2018, so saying that they are the "first" vector database is just flat out wrong since Pinecone was founded in 2019.
Re: Vector search just got up to 10x faster and vertically scalable
#15Confused by their claim to be the 'first' vector database. These things have been around forever? For example FLANN (not a DB server, but example lib) is from 2009
I think the difference is in the layer of abstraction i.e. FLANN is just the underlying search functionality whereas vector databases are fully managed solutions. Even so, Weaviate came out in 2018, so saying that they are the "first" vector database is just flat out wrong since Pinecone was founded in 2019.
Weaviate calling themselves a vector database is a fairly new thing.
Re: Vector search just got up to 10x faster and vertically scalable
#1610x faster with respect to what?
Re: Vector search just got up to 10x faster and vertically scalable
#17Earlier quoted context omitted.
If you really think that's enough to build a real product, go for it. Even open-source companies (Elastic, Mongo, Scylla) have to build tons of infra around their core codebase in order to make it an actual cloud product.
Not that easy, the founder was a director at AWS. This is just devops/obfuscation on top of an open source library: FAISS
Pinecone doesn’t use Faiss, nor ScaNN. We love Faiss and even teach people to use it[1]. There happens to be a sizable population of engineers who need more than what Faiss provides (like live index updates and metadata filtering, for example), and can’t be bothered or aren’t being paid to customize and manage open-source libraries all day.
Re: Vector search just got up to 10x faster and vertically scalable
#18Re: Vector search just got up to 10x faster and vertically scalable
#19Earlier quoted context omitted.
I think the difference is in the layer of abstraction i.e. FLANN is just the underlying search functionality whereas vector databases are fully managed solutions. Even so, Weaviate came out in 2018, so saying that they are the "first" vector database is just flat out wrong since Pinecone was founded in 2019.
Weaviate calling themselves a vector database is a fairly new thing.
The fact that Weaviate only recently started calling themselves a vector database is completely irrelevant here. They had this type of vector data infrastructure before Pinecone did, and that's all that matters.
Example: I'm going to start a new company called Conifercone and do pretty much exactly what you do, but call it a "vector datastore" instead. Apparently I've now created the first ever vector datastore even though functionally I have done nothing novel.
Re: Vector search just got up to 10x faster and vertically scalable
#20Quoted post unavailable.
Which open source libraries is pinecone wrapping?
I’m not sure where the other commenter gets their confidence, but Pinecone is not wrapping any open source vector-search library. We offer three index types (in-memory, in-memory graph-based, hybrid memory + disk), and all are proprietary.
We do have articles about Faiss and HNSW and all sorts of other vector-search and NLP topics, so it’s possible that’s where the confusion comes from.