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Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is t

Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).

m1117 4y ago
Andreessen horowitz should've just googled
moab 4y ago
Spot on. There is zero moat and the self-hosted alternatives are rapidly improving (if not better) than Pinecone. There are good open-source contributions coming from bigcorp beyond Meta too, e.g., DiskANN (https://github.com/microsoft/DiskANN https://github.com/microsoft/DiskANN).
- zzzzzzzza 4y ago
  why use this instead of something like pgvector?
findjashua 4y ago
i mean it’s Andreesen. They’re like the Softbank of Silicon Valley
chadash 4y ago
Oracle DB has quite a few free alternatives. Yet Larry Ellison is the world's 4th wealthiest person.
mmq 4y ago
Most demos shared by people can use numpy arrays similar to this https://twitter.com/karpathy/status/1647374645316968449 https://twitter.com/karpathy/status/1647374645316968449
- bugglebeetle 4y ago
  It’s true, but I also wouldn’t want any developer beside Karpathy to implement a production service using numpy arrays (I use Faiss).
teaearlgraycold 4y ago
It has a moat for those that start using it. Vendor lock in.
nemothekid 4y ago
Maybe I am fundamentally missing something, but a "cloud database company" seems like the most boring tech? No one is calling Planetscale or Yugabyte nonsense because there are free alternatives like Postgres.
- AYBABTME 4y ago
  To be fair PlanetScale is a whole lot more than hosted MySQL.
boc 4y ago
You're telling me the VC that went hog-wild on NFTs and Crypto is fomo'ing into AI without any DD? I'm shocked.
- deleted 4y ago
  [deleted]
jhj 4y ago
> Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector) Faiss is a collection of algorithms for in-memory exact and approximate high-dimensional (e.g., > ~30 dimensional) dense vector k-nearest neighbor, it doesn't add or really consider persistence (beyond full index serialization to an in memory or on disk binary blob), fault tolerance, replication, domain-specific autotuning and the like. The "vector database" companies like Pinecone, Weviate, Zilliz and what not will add these other features to turn them into a complete service, they're not really the same. pgvector seems to be DB-backed IndexFlat and IndexIVFFlat (?) from the Faiss library at present but is of course not a complete service. However which kind of approximate indexing you want to use very much depends upon the data you're indexing, and where in the tradeoff space between latency, throughput, encoding accuracy, NN recall and memory/disk consumption you want to be (these are the fundamental tradeoffs in the vector search domain), and whether you are performing batched queries or not. To access the full range of tradeoffs you'd need to use all of the options which are available in Faiss or similar low-level libraries which may be difficult to use or require knowledge of underlying algorithms. (I'm the author of the GPU half of Faiss)

m1117 4y ago

Andreessen horowitz should've just googled

moab 4y ago

Spot on. There is zero moat and the self-hosted alternatives are rapidly improving (if not better) than Pinecone. There are good open-source contributions coming from bigcorp beyond Meta too, e.g., DiskANN (https://github.com/microsoft/DiskANN https://github.com/microsoft/DiskANN).

zzzzzzzza 4y ago
why use this instead of something like pgvector?

findjashua 4y ago

i mean it’s Andreesen. They’re like the Softbank of Silicon Valley

chadash 4y ago

Oracle DB has quite a few free alternatives. Yet Larry Ellison is the world's 4th wealthiest person.

mmq 4y ago

Most demos shared by people can use numpy arrays similar to this https://twitter.com/karpathy/status/1647374645316968449 https://twitter.com/karpathy/status/1647374645316968449

bugglebeetle 4y ago
It’s true, but I also wouldn’t want any developer beside Karpathy to implement a production service using numpy arrays (I use Faiss).

teaearlgraycold 4y ago

It has a moat for those that start using it. Vendor lock in.

nemothekid 4y ago

Maybe I am fundamentally missing something, but a "cloud database company" seems like the most boring tech? No one is calling Planetscale or Yugabyte nonsense because there are free alternatives like Postgres.

AYBABTME 4y ago
To be fair PlanetScale is a whole lot more than hosted MySQL.

boc 4y ago

You're telling me the VC that went hog-wild on NFTs and Crypto is fomo'ing into AI without any DD? I'm shocked.

deleted 4y ago
[deleted]

jhj 4y ago

> Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector) Faiss is a collection of algorithms for in-memory exact and approximate high-dimensional (e.g., > ~30 dimensional) dense vector k-nearest neighbor, it doesn't add or really consider persistence (beyond full index serialization to an in memory or on disk binary blob), fault tolerance, replication, domain-specific autotuning and the like. The "vector database" companies like Pinecone, Weviate, Zilliz and what not will add these other features to turn them into a complete service, they're not really the same. pgvector seems to be DB-backed IndexFlat and IndexIVFFlat (?) from the Faiss library at present but is of course not a complete service. However which kind of approximate indexing you want to use very much depends upon the data you're indexing, and where in the tradeoff space between latency, throughput, encoding accuracy, NN recall and memory/disk consumption you want to be (these are the fundamental tradeoffs in the vector search domain), and whether you are performing batched queries or not. To access the full range of tradeoffs you'd need to use all of the options which are available in Faiss or similar low-level libraries which may be difficult to use or require knowledge of underlying algorithms. (I'm the author of the GPU half of Faiss)