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    Pinecone Vector Database - Annual Commit

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    Sold by: Pinecone 
    *only for accepting private offers. Pinecone is a fully managed serverless 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 a fully managed vector database that makes it easy to add vector search to production applications. It 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.

    Usage-based Billing You will be billed at the end of the month for storage consumed. More information can be found at https://www.pinecone.io/pricing/ 

    Annual Commitments Purchasing this product involves an annual commitment which allows you to purchase Pinecone with volume-based discounts. Please first reach out to your sales representative or https://www.pinecone.io/contact/  to discuss custom pricing and discounts before placing an order on this page.

    To get started without an annual commitment, please go to Pinecone's Pay As You Go product listing.

    Highlights

    • The Pinecone Vector Database provides fast, fresh, and filtered vector search: Ultra-low query latency, even with billions of items. Live index updates when you add, edit, or delete data. Combine vector search with metadata filters for more relevant and faster results.
    • Enterprise-grade security and compliance: SOC 2 Type II certified, GDPR-ready, and built to keep data from your Vector Database secure.
    • Fully managed and Easy to use: Get started with an easy-to-use API or the Python client. No need to maintain infrastructure, monitor services, or troubleshoot algorithms.

    Details

    Delivery method

    Deployed on AWS

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    Features and programs

    Financing for AWS Marketplace purchases

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    Pricing

    Pinecone Vector Database - Annual Commit

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    Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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    Dimension
    Description
    Cost/12 months
    Overage cost
    Commit
    Total Commitment Value
    $100,000.00

    AI Insights

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    Dimensions summary

    The "Commit" dimension on AWS Marketplace represents an annual financial commitment to Pinecone's vector database service, offering volume-based discounts compared to pay-as-you-go pricing. While the specific discount structure requires discussion with Pinecone's sales team, the commitment covers the same core pricing components: serverless compute usage (measured in Read, Write, and Store Units), and data transfer costs. Customers should contact Pinecone directly to determine their optimal commitment level based on expected usage patterns before proceeding with the annual subscription through AWS Marketplace.

    Top-of-mind questions for buyers like you

    What is the annual commitment option on AWS Marketplace, and how does it differ from pay-as-you-go?
    The annual commitment option allows customers to receive volume-based discounts by committing to a predetermined spending level for one year. The exact discount structure is customized based on expected usage patterns and requires discussion with Pinecone's sales team before purchasing through AWS Marketplace.
    How is billing calculated under the annual commitment plan?
    Usage is still measured and billed monthly based on actual consumption of serverless compute (Read, Write, and Storage Units), and data transfer. The annual commitment establishes a minimum spending threshold that provides access to discounted rates compared to standard pay-as-you-go pricing.
    What should I do before purchasing the annual commitment plan on AWS Marketplace?
    You should contact Pinecone's sales team through their website to discuss your expected usage patterns and receive a customized quote with volume-based discounts. This consultation will help determine the appropriate commitment level and ensure you understand the potential cost savings compared to pay-as-you-go pricing.

    Vendor refund policy

    Please contact us at support@pinecone.io 

    Custom pricing options

    Request a private offer to receive a custom quote.

    How can we make this page better?

    We'd like to hear your feedback and ideas on how to improve this page.
    We'd like to hear your feedback and ideas on how to improve this page.

    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) .

    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.

    Usage information

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    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

    Vendor resources

    Support

    Vendor support

    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. support@pinecone.io  support@pinecone.io 

    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.

    Product comparison

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    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
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    12 reviews
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    Overview

     Info
    AI generated from product descriptions
    Vector Search Performance
    Supports ultra-low query latency with vector search capabilities for billions of items
    Real-time Index Management
    Enables live index updates for adding, editing, and deleting data dynamically
    Metadata Filtering
    Provides advanced filtering capabilities to combine vector search with metadata for enhanced search relevance
    Distributed Infrastructure
    Utilizes distributed infrastructure design to ensure high performance and reliability at scale
    Security Compliance
    Offers enterprise-grade security with SOC 2 Type II certification and GDPR readiness
    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

    Contract

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    Standard contract
    No
    No
    No

    Customer reviews

    Ratings and reviews

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    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.
    Mohit G.

    idéal pour l'apprentissage automatique, les applications d'IA et la recherche de similarité

    Reviewed on Sep 12, 2024
    Review provided by G2
    Qu'aimez-vous le plus Ă  propos de the product?
    Il est spécialisé dans les cas d'utilisation pilotés par l'IA avec une recherche en temps réel et à faible latence offrant une intégration transparente dans les flux de travail d'apprentissage automatique avec une infrastructure évolutive optimisée pour les données non structurées et semi-structurées dans les applications d'IA.
    Que n’aimez-vous pas à propos de the product?
    Il a un focus limité qui est uniquement lié aux données vectorielles sans focus majeur sur l'intelligence d'affaires dans l'outil de transformation de données. De plus, son cas d'utilisation est un peu complexe avec un manque d'intégration de l'écosystème.
    Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
    C'est résoudre le problème lié aux données vectorielles d'IA générées par l'application.
    Akhil G.

    Dieu de la création des embeddings

    Reviewed on Sep 11, 2024
    Review provided by G2
    Qu'aimez-vous le plus Ă  propos de the product?
    quand je crée des embeddings, comparé à d'autres produits, cela semble sans tracas et bon marché.
    Que n’aimez-vous pas à propos de the product?
    Je suis le testeur bĂŞta de l'assistant AI Pinecone, il n'est pas prĂŞt pour la production, donc il semble ĂŞtre uniquement pour les tests, j'attends la version prĂŞte pour la production.
    Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
    fonctions sans tracas et ensembles de données d'embeddings
    Satwik L.

    Utilisateur bĂŞta de l'assistant Pinecone

    Reviewed on Sep 10, 2024
    Review provided by G2
    Qu'aimez-vous le plus Ă  propos de the product?
    J'ai utilisé Pinecone pour les embeddings et c'est moins cher et fiable par rapport à d'autres services d'embeddings.
    Que n’aimez-vous pas à propos de the product?
    Je n'aime pas l'impression générale qui semble légère pour la documentation du service produit.

    J'adore voir l'assistant Pinecone en version déployable car il est puissant, mais il est uniquement en version bêta pour les tests, pas pour la production.
    Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
    Créer des embeddings facilement sans coût élevé.

    Bon soutien de l'équipe.
    Carlos O.

    Option solide pour la base de données vectorielle

    Reviewed on Aug 28, 2024
    Review provided by G2
    Qu'aimez-vous le plus Ă  propos de the product?
    Très fiable et rapide. Prix compétitif.
    Que n’aimez-vous pas à propos de the product?
    Peut-être que quelques fonctionnalités supplémentaires seraient agréables, et un peu plus de clarté sur son algorithme AKNN, qui est caché à l'utilisateur.
    Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
    Trouver des documents scientifiques dans de très grands volumes de données.
    Stephen C.

    Pinecone : L'épine dorsale de la recherche et de la récupération de vecteurs efficaces

    Reviewed on Aug 23, 2024
    Review provided by G2
    Qu'aimez-vous le plus Ă  propos de the product?
    Pinecone excelle dans la fourniture d'une expérience de recherche vectorielle fluide et performante. Sa facilité d'utilisation, combinée à des fonctionnalités puissantes telles que les mises à jour en temps réel et l'évolutivité, en fait une solution de choix pour gérer des données vectorielles complexes. La capacité à s'intégrer sans effort aux flux de travail existants et son support client de premier ordre sont des points forts certains.
    Que n’aimez-vous pas à propos de the product?
    Bien que Pinecone soit robuste, le prix peut être un peu élevé pour les projets plus petits ou les startups. De plus, un contrôle plus granulaire sur les options d'indexation améliorerait la personnalisation pour les utilisateurs avancés. Cependant, les avantages l'emportent largement sur ces inconvénients mineurs.
    Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
    Pinecone résout le défi complexe de la recherche vectorielle efficace et évolutive. À une époque où la gestion de grands volumes de données à haute dimension est cruciale, la capacité de Pinecone à indexer, rechercher et récupérer des vecteurs rapidement et avec précision change la donne. Pour nous, cela signifie des réponses aux requêtes plus rapides, une précision accrue dans la récupération des données et la possibilité de se concentrer sur la création de meilleurs produits plutôt que sur la gestion de l'infrastructure. La solution de Pinecone a considérablement réduit le temps et les efforts nécessaires pour gérer et rechercher des données vectorielles, permettant à notre équipe d'être plus productive et innovante.
    View all reviews