I recently started using Pinecone and was impressed with how user-friendly it is, especially for someone new to vector databases. Its standout feature is its focus on doing one thing exceptionally well. The documentation is clear and easy to follow, making the setup process smooth. Both indexing and query times are impressively fast, which significantly enhances efficiency. I chose Pinecone over other options because it supports larger vector sizes, a key requirement for my needs. Highly recommend Pinecone for its simplicity, speed, and capabilities. Review collected by and hosted on G2.com.

There are a couple of areas where Pinecone could improve. First, the options for datacenter hosting are limited. For instance, if using AWS, it currently only supports the us-east-1 region, which can be restrictive. Second, the console lacks robust security measures for critical actions. Adding a Multi-Factor Authentication (MFA) verification for deleting indexes and projects would enhance security and prevent accidental data loss. Review collected by and hosted on G2.com.

The things I mostly like are:

- that is easy to set up by following the docs

- fast for loading and updating embeddings in the index

- easy to scale if needed Review collected by and hosted on G2.com.

- that is not open source

- I cannot query the full list of ids from an index (I needed to build a database and a script to track what products I have inside the index)

- customer support by mail takes too much time Review collected by and hosted on G2.com.

We did a lot of research on vector databases at Refsee.com and tried many things: embedded db into the docker image served at AWS Lambda (believe me, that's not what you want), Milvus, Pinecone etc.

We always had problems and necessity of extra tuning before, both with self-hosted OSS dbs and managed ones, but Pinecone really did the trick! It just works! Review collected by and hosted on G2.com.

As usual, if you choose managed solution you get a vendor lock. Probably can be costly if you scale and no option for on-prem installation Review collected by and hosted on G2.com.

Excellent user interface, excellent supporting materials and literature to learn, very easy to use, improving quite quickly. It is quite easy to implement it in integration with our existing workflow. I use it for all vector database operations. Review collected by and hosted on G2.com.

I have some very technical questions, like: will hybrid search ALWAYS be limited to dot product? But these are quite few. Review collected by and hosted on G2.com.

It is very easy to integrate the Pinecone API with a text generation application using LLM. Semantic search is very fast and allows more complex queries using metadata and namespace. I also like the comprehensive documentation. Review collected by and hosted on G2.com.

For organizations that need only a little more capacity than is available in a single free pod, the pricing may be more favorable. Review collected by and hosted on G2.com.

I have a Pinecone index that I've had to double in size three times now to handle the nearly 10 million vectors I have stored. Despite the increase in size, the search speed has remained constant, and upsert speed has actually increased. Review collected by and hosted on G2.com.

This may not be unique to Pinecone, but you need to make sure you figure out your data schema up front because it requires some work to change records at scale if you want to add or modify metadata. Review collected by and hosted on G2.com.

I really appreciate how Pinecone makes it easy to integrate vector search into applications. Its cloud-native setup and simple API mean I don't have to worry about infrastructure issues. Also, the performance is fantastic, even with massive amounts of data, and the low latency is a huge plus. Review collected by and hosted on G2.com.

Being relatively new, it lacks some features and integrations compared to more established databases. And, there's a bit of a learning curve to fully leverage its capabilities. Additionally, there are some limitations regarding customization and exportability of vectors outside of Pinecone. Review collected by and hosted on G2.com.

Pinecone is fast and fully managed. It also allows you to duplicate your index and create a new one. It was well suited for us. Review collected by and hosted on G2.com.

It provides inaccurate search results even for simple semantic search. Review collected by and hosted on G2.com.

The ease of use to get integrated with Pinecone was pretty incredible. We were up and running with a vector database in no time. Review collected by and hosted on G2.com.

At first, the UI lacked some features that seemed like a must, but they've added a lot of what we were looking for and seem to be actively developing it. Review collected by and hosted on G2.com.

Pinecone has helped our company, fevr.io, scale our semantic chat functionality across three key regional markets. The responsiveness and ease of implementation has been a huge plus for our developers. The documentation has been very helpful as well, especially in terms of integrations with products like OpenAI and Langchain. Add to that, the customer support has been tremendously useful. Review collected by and hosted on G2.com.

While not necessarily a negative feedback, having even more research data on how different dimensions and pods affect various responses would be a helpful resource to have as a reference. Review collected by and hosted on G2.com.