Reviews from AWS Marketplace
0 AWS reviews
-
5 star0
-
4 star0
-
3 star0
-
2 star0
-
1 star0
External reviews
External reviews are not included in the AWS star rating for the product.
User and Developer-friendly Vector Database that has helped our company scale
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Storing embeddings of documents is quite costly and difficult to manage. Pinecone solves this with solutions that are easy to implement with OpenAI's API. It allows for rapid prototyping of custom chat models.
- Leave a Comment |
- Mark review as helpful
Vector database that just works
What do you like best about the product?
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!
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!
What do you dislike about the product?
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
What problems is the product solving and how is that benefiting you?
We do vector search over our own datasets – basically a "google images" on our own data
Efficient and user-friendly, Ideal for vector database newcomers
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Pinecone plays a crucial role in our workflow by efficiently storing vectors from OpenAI Embeddings. This capability allows us to effectively identify and link related content across various features of our platform. The result is a more cohesive and intuitive user experience, as we can seamlessly connect relevant information and offerings. This not only enhances our platform's functionality but also significantly improves user engagement and satisfaction.
Useful product for those who know what to do with it.
What do you like best about the product?
It is a fast and efficient vector database.
What do you dislike about the product?
The web-interface leaves many features to be desired.
It is quite a bit on the pricier side.
It is quite a bit on the pricier side.
What problems is the product solving and how is that benefiting you?
We use it to hold educational material
Solid Hosted Vector DB
What do you like best about the product?
Ease of deployment! It takes just a few minutes to get an index set up and deployed.
What do you dislike about the product?
The web-based API console could be improved, for example for experiments with metric (cosine vs dotproduct vs euclidean).
What problems is the product solving and how is that benefiting you?
Storing embeddings for RAG.
Great vector database that has the necessary compliance
What do you like best about the product?
It's very reliable, easy to set up and has both SOC 2 and HIPAA compliance.
What do you dislike about the product?
No way to see the list of all the IDs in your collection.
What problems is the product solving and how is that benefiting you?
Handling similarity searches
I couldn't be more pleased
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
Fast speed and fully managed. I don't have to worry about anything other than paying the bill.
Best vector DB
What do you like best about the product?
- Its retrieval process is good compared to other vector DB
- We can visualize it in UI
- We can visualize it in UI
What do you dislike about the product?
It could have been open source which can make it easily usable with high demand.
What problems is the product solving and how is that benefiting you?
Doc search and embedding storage and text retrival
Vector Database
What do you like best about the product?
Pinecone used for indexing or searching of duplicate documents or similarity search score with our query. It helps to detect the anamolies easily. Mostly i liked this database to store my data as a vector form.
What do you dislike about the product?
Pinecone premium subscription for various indexes and pods control.
What problems is the product solving and how is that benefiting you?
Helps me to easily upsert vectorized data to pinecone vector Db.
showing 21 - 29