External reviews are not included in the AWS star rating for the product.
We've been building an ERP dashboard using generative UI. We needed a vector database to retrieve and implement augmentation, so we opted to use Pinecone.
We chose Pinecone because it covers most of the use cases. Also, Pinecone is stable and reliable.
We are using Pinecone for retrieval. Pinecone did a really great job in marketing and perfecting its adoption. That was very helpful because we could find resources if we got stuck on a problem. The only reason we are not using Quadrant, despite its promising features and reliable performance, is its limited resources. Pinecone community has been around for a lot longer than the Quadrant community.
We chose Python so that any new feature we could add could be implemented easily. Since Python has been around for a while, plenty of options are available. Some tutorials and resources, such as blog posts, provide references for implementing new features. We haven't utilized anything specific to Pinecone that only Pinecone offers.
The tool collects data, adds it to the database, and retrieves it using its SDK.
Onboarding could be better and smoother. Navigation is difficult because most of us rely on watching tutorials on YouTube to understand how to use this software. The onboarding journey should explain more topics.
We are currently using it.
The solution is stable. We use it for enterprise purposes. It's reliable for our use case. We haven't experienced any downtime or significant latency issues.
We use the tool for a single project with 10-15 people.
We worked with PG vector. We were using Sophos and a free directory plugin. We used it for testing and building the prototype. When I built it, we opted for more widely adopted services. We chose a database geared towards storing and retrieving active data, especially in augmenting generation.
The initial setup is great.
The scope of the project was really small to opt for positives with the PG vector plug-in. We opted for Pinecone since it is popular, and has a better use case.
The main issue arises when our team members join, and we must guide them, especially those unfamiliar with Pinecone. We assign them a small project to explore the software independently. This helps them overcome any hurdles and gain a deeper understanding of how to utilize Pinecone effectively. However, despite its overall positive aspects, there's room for improvement, particularly in making it more minimalistic and simplifying access to various options. Like many SaaS products, setting it up can be time-consuming. It should provide clear instructions or a step-by-step guide for undertaking small projects independently.
Real-time data retrieval is good. However, it used to drop in a while. Overall, it was reliable.
We don't require a lot of maintenance on the project. It's a small-scale project, and the scope is specific and small. There haven't been any issues. Two to Three people are enough for the solution's maintenance.
I recommend the solution and advise you to explore the documentation and tutorials. It's easy to pick up and integrate.
Overall, I rate the solution an eight out of ten.
In my company, we store our industry documents in Pinecone. My company stores the PDF files in Pinecone to use for the RAG application.
The most valuable features of the solution are similarity search and maximal marginal relevance search for retrieval purposes.
The product fails to offer a serverless type of storage capacity. From an improvement perspective, the storage capacity of the tool should not be pod-based.
I have been using Pinecone for years. I am an end user of the solution.
It is a stable solution. Stability-wise, I rate the solution an eight out of ten.
Around four or five people in my company use the product.
The solution is used on a daily basis in my company.
I don't have any previous experience with any other solutions other than Pinecone.
The solution is deployed on an on-premises model.
The solution can be deployed in a day.
My company is currently evaluating Elasticsearch against Pinecone.
My company has integrated Pinecone into our machine-learning workflow by using LangChain. My company also uses an OCR feature to detect PDF files, which we added to Pinecone.
A chatbot application is the specific AI application for which Pinecone is used in our organization since it provides us with a source of knowledge through RAG.
I am unsure if Pinecone's similar search capabilities have enhanced our data analysis since my company is still in the middle of the tool's production phase.
If I measure Pinecone's impact on our company's system performance and scalability, I would rate it at an eight on a scale of one to ten.
I rate the overall tool an eight out of ten.
We recently made the switch to Pinecone database for our vector search needs, and we couldn't be happier with the results! The latencies are lower than we expected, making it a fast and reliable solution for us. Additionally, the metadata filtering works out of the box which is crucial for e-commerce. Overall, we highly recommend Pinecone to anyone in need of an efficient and user-friendly vector search solution.
Pinecone is a great service for anyone who needs fast and accurate vector search for their applications. I have been using Pinecone for a few months now and I am very impressed by its features and performance.
It is easy to manage multiple user accounts with Pinecone. I can invite my team members to join my projects and assign them different roles and permissions. I can also monitor their activities and usage through the web console.
It is good to have a support experience with Pinecone. They have a friendly and responsive team that is always ready to help me with any issues or questions. They also have a comprehensive documentation and a community forum where I can find answers and tips.
The Pinecone pay as you go marketplace offering made it easy for us to quickly get up and running to do our evaluation of the tool. The pricing link to their website in the marketplace description is easy to understand and accurate based on our usage of the tool.