Sold by: PineconeÂ
Pinecone is a fully managed vector database that makes it easy to add vector search to production applications. The Pinecone Vector Database combines state-of-the-art vector search libraries, advanced features such as filtering, and distributed infrastructure to provide high performance and reliability at any scale. No more hassles of benchmarking and tuning algorithms or building and maintaining infrastructure for vector search.
Overview
Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Learn more at: https://www.pinecone.ioÂ
The Standard plan incurs a monthly minimum charge of $50. Once your usage exceeds the $50 minimum you will pay-as-you-go. Subscribing through the AWS Marketplace automatically upgrades your Pinecone organization to the Standard plan.
Usage credits will be applied towards serverless, inference, and assistant usage. Additional usage will be billed as you go.
Billing: See details at: https://www.pinecone.io/pricingÂ
Note: The "Pinecone Billing Unit" listed below is an AWS Marketplace requirement and does not reflect the actual cost or metering of costs for Pinecone.
Highlights
- The Pinecone serverless vector database is the developer-favorite vector database that is easy to use at any scale, with a large user community. Fully managed vector database with intuitive API, console, and SDKs.
- The Pinecone serverless vector database provides best-in-class performance with 50x lower cost at any scale. Pinecone delivers fast vector search with filtering, live index updates, and keyword boosting (hybrid search).
- Pinecone is the most popular vector database for AI search, recommenders, and Retrieval Augmented Generation (RAG) applications. Enterprise-grade security and compliance: SOC 2 Type II and HIPAA certified and built to keep data from your Vector Database secure
Details
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Delivery method
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
Pinecone Billing Unit | $0.01 |
Dimensions summary
Pinecone Vector Database uses a single dimension called "Pinecone Billing Unit" which represents their consumption-based pricing model. Based on Pinecone's documentation, this billing unit aggregates costs across different usage metrics including read units (RUs), write units (WUs), and storage for serverless indexes. Additional costs may apply for operations like data imports, backups, and AI model inference services.
Top-of-mind questions for buyers like you
What is a Pinecone Billing Unit and how is it calculated?
A Pinecone Billing Unit represents the aggregated consumption across different usage metrics including read operations (RUs), write operations (WUs), and storage for serverless indexes.
Is there a minimum usage commitment for Pinecone?
Yes, Pinecone requires a minimum usage commitment of $50/month for Standard plans and $500/month for Enterprise plans, with customers being charged only for actual usage if it exceeds these minimums.
How does Pinecone charge for different types of operations?
Pinecone charges based on the type of operation - read units for queries and fetches, write units for data modifications, storage costs per GB, and additional charges for specialized services like embedding and reranking models.
Vendor refund policy
Please contact support@pinecone.ioÂ
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Support
Vendor support
After creating your organization through the AWS Marketplace and signing into Pinecone, you may need to switch to your new organization. You can do so via the Switch Organization toggle in the left-side panel of the Pinecone console, directly above Settings.
After accessing your organization, you must create a new project if you wish to create non-starter indexes (docs.pinecone.io/docs/create-project).
If your AWS organization already has a subscription, please request an organization admin to invite you via the Pinecone console. You do not need to create a new Pinecone organization to join your team.
This is a fully managed service with technical support included with Standard and Enterprise plans. For more information regarding support SLAs, please see each plan's details on the pricing page (pinecone.io/pricing).
https://docs.pinecone.io/troubleshooting/how-to-work-with-supportÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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By Weaviate
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Vector Search Capability
Advanced vector search library with distributed infrastructure for high-performance search operations
Filtering Mechanism
Supports advanced filtering capabilities with live index updates and keyword boosting for hybrid search
Scalability Architecture
Fully managed vector database infrastructure designed to handle search and retrieval at any scale
Security Compliance
Enterprise-grade security with SOC 2 Type II and HIPAA certification for data protection
AI Application Integration
Optimized for AI search, recommender systems, and Retrieval Augmented Generation (RAG) applications
Vector Search Capability
High-performance vector search engine with advanced embedding storage and retrieval mechanisms
Metadata Filtering
Extended filtering support on additional metadata fields alongside vector embeddings
Open-Source Architecture
Fully open-source vector database with flexible deployment and scalability options
Neural Network Integration
Native support for neural network encoders and embedding transformations
API-Driven Design
Convenient programmatic interface for storing, searching, and managing vector data
Vector Database
Low-latency vector database supporting multimodal media types including text and images
Search Capabilities
Advanced vector similarity search, hybrid search, and filtered search functionality
AI Model Integration
Optional integrations with multiple AI platforms including SageMaker, Bedrock, OpenAI, Cohere, Anthropic, and HuggingFace
Cloud Architecture
Cloud-native database with fault tolerance and serverless infrastructure
Programming Language Support
Accessible through multiple client-side programming languages for flexible implementation
Standard contract
No
No
No
Customer reviews
4.5
27 ratings
27 AWS reviews
|
42 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Vibhu
complicated set-up
Reviewed on Dec 09, 2024
Review from a verified AWS customer
When I tried to use the Pinecone standard plan connected with AWS Marketplace, the setup process looped between Pinecone and AWS Marketplace. I am unable to start a standard plan. It still showing current plan as starter eventhough the pinecone documents says AWS Marketplace don't support it.
Apart from the chatbot, there is no help from the pinecone side. There has been no response to my sales query also.
Mohit G.
ideal for machine learning, AI applications and similarity search
Reviewed on Sep 12, 2024
Review provided by G2
What do you like best about the product?
It is specialised in AI driven use cases with real time and low latency search giving seamless integration into machine learning workflows with scalable infrastruture optimized for unstructured and semi-structured data in AI applications.
What do you dislike about the product?
It has limited focus that is related only with the vector data with no major focus on Business intelligence in data transformation tool.
Also it's use case is little complex with lack of ecosystem integration.
Also it's use case is little complex with lack of ecosystem integration.
What problems is the product solving and how is that benefiting you?
It is solving the issue related with AI vector data generated from the app.
Akhil G.
God of creating embeddings
Reviewed on Sep 11, 2024
Review provided by G2
What do you like best about the product?
when iam creating embeddings,compared to other products,it feels hassle free& cheap.
What do you dislike about the product?
I am the beta tester of pinecone AI assiatant,it is not production ready so it feels like only for testing,i am expecting for the production ready version.
What problems is the product solving and how is that benefiting you?
hassle free functions and embeddings data sets
Satwik L.
Pinecone assistant beta user
Reviewed on Sep 10, 2024
Review provided by G2
What do you like best about the product?
I have been using pinecone for embeddings and it is cheaper and reliable compared to other embedding services.
What do you dislike about the product?
I dislike the overall feel which feels lightweighed for the product service documentation.
I love to see pinecone assistant in deployable version because it is powerful yet it is in the beta version only for testing not for production
I love to see pinecone assistant in deployable version because it is powerful yet it is in the beta version only for testing not for production
What problems is the product solving and how is that benefiting you?
Creating embeddings at ease without any big pricing.
Good support from team.
Good support from team.
Carlos O.
Solid option for vector DB
Reviewed on Aug 28, 2024
Review provided by G2
What do you like best about the product?
Easy to use. very reliable and fast. Competitive price
What do you dislike about the product?
Maybe some extra features would be nice, and some more clarity into its AKNN algo, which is hidden from the user
What problems is the product solving and how is that benefiting you?
Finding scientific documents in very large volumes of Data.