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Pinecone description
Pinecone is a cloud-based database designed specifically for AI applications. Unlike traditional databases, it focuses on storing and quickly searching through "vectors," which are mathematical representations of data like text, images, or audio. This allows companies to build AI features that can, for example, instantly find the most relevant information from millions of documents, power accurate recommendation systems, or analyze complex patterns. Pinecone manages all the technical aspects, so developers can focus on building their applications without worrying about infrastructure.
Who is using Pinecone?
Who is Pinecone best for
Pinecone is a cloud-based vector database tailored for AI applications. It allows developers to easily store and search through vectors, enabling features like powerful semantic search and recommendation systems. Users praise its speed, ease of use, and excellent support, while some note limitations in ecosystem integration and pricing for smaller projects.
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Best for startups and smaller companies needing AI-powered search.
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Ideal for software companies developing AI applications.
Pinecone features
| Supported Pinecone offers tools for creating, managing, and optimizing indexes, including features like upserting, querying, and metadata filtering. |
| Supported Pinecone supports vector similarity search with its API and k-NN algorithm. |
| Supported Pinecone allows for both vertical and horizontal scaling in the cloud. |
| Supported Pinecone allows scaling database capacity up via vertical and horizontal scaling. |
We evaluate the sentiment that users express about non-functional aspects of the software
Value and Pricing Transparency
Customer Service
Ease of Use
Reliability and Performance
Ease of Implementation
Scalability
Pinecone reviews
We've summarised 36 Pinecone reviews (Pinecone G2 reviews) and summarised the main points below.
- Excellent for AI/ML applications and similarity search.
- Hassle-free and cheap embedding creation.
- Reliable and fast with competitive pricing.
- High performance with upsert and search in milliseconds.
- Simple integration via API and deployment.
- Incredible support.
- Useful metadata features.
- Serverless indexes simplify maintenance and scaling.
- Free limited indexes for development.
- Affordable serverless pricing for startups.
- Supports large embeddings, sparse & dense embeddings, and fast queries.
- Great user interface and learning resources.
- Easy workflow integration.
- Fast and stable with good uptime.
- Seamless, high-performance vector search.
- Real-time updates and scalability.
- Effortless workflow integration and top-notch support.
- Sparse-Dense offering improves retrieval quality.
- Excellent documentation and tutorials.
- User-friendly, especially for vector database newcomers.
- Good documentation and Python SDK.
- Production-ready with low latency.
- Good integration with AI/LLM ecosystem.
- Responsive and easy implementation.
- Helpful documentation and integrations with OpenAI and Langchain.
- SOC 2 and HIPAA compliant.
- Limited ecosystem integration and complex use cases.
- Pinecone Assistant is not production-ready.
- Documentation feels lightweight.
- Limited clarity on AKNN algorithm.
- Limited metadata documentation and single-stage queries.
- Smart bot support is less effective than alternatives like ChatGPT.
- Occasional downtime.
- Pricing can be steep for smaller projects.
- 10,000 namespace limit on the serverless instance.
- Difficult metadata management.
- Web interface needs improvement.
- Limited data center location options and lack of MFA.
- Inaccurate search results for semantic queries.
- No Azure support.
- No easy way to export all vectors.
- Tricky pricing structure.
- Limited features and integrations compared to established databases.
- Learning curve to fully leverage capabilities.
- Customization and vector exportability limitations.
Pinecone pricing
The commentary is based on 16 reviews from Pinecone G2 reviews.
Pinecone's pricing is generally considered competitive and affordable, especially its serverless option. While some users find the pricing structure complex or expensive for large-scale deployments, many appreciate the free tier for smaller projects and development. Overall, Pinecone is praised for its cost-effectiveness relative to performance.
Users sentiment
See the Pinecone pricing page.
Pinecone alternatives
QdrantOpen-source, offering more flexibility for customization and deployment. Has stronger momentum in its team growth. Better for e-commerce, marketing, and advertising use cases. A Pinecone competitor and alternative.Read more
OrbBetter for managing billing and revenue, especially for subscription or usage-based models. Geared towards fast-growing businesses with complex pricing needs. Has more momentum currently. A Pinecone competitor and alternative for billing automation.Read more
MyScaleMyScale is growing faster and uses familiar SQL, potentially easing integration for users already working with SQL databases. It aims for cost-effectiveness and faster AI application development. However, it has fewer user reviews and no ratings data available. A Pinecone alternative or competitor for those comfortable with SQL.Read more
Microsoft SQL ServerBetter for structured data and traditional applications. Wider industry applicability. More mature and established SQL Server alternative. Has slower momentum.Read more
Google Cloud BigQueryBetter for structured data analysis and business intelligence. SQL-based, easier for users familiar with traditional databases. More broadly applicable across various industries. Negative pricing sentiment.Read more
MongoDB AtlasBetter suited for general purpose database needs, not specifically vector search. A Pinecone alternative or competitor for those less focused on AI/ML applications. Wider industry applicability but less specialized.Read more
Pinecone FAQ
What is Pinecone and what does Pinecone do?
Pinecone is a vector database built for AI applications. It allows efficient storage and search of vectors, which are mathematical representations of data like text and images. This enables building AI features such as semantic search, recommendation systems, and anomaly detection. Pinecone's managed service simplifies infrastructure management for developers.
How does Pinecone integrate with other tools?
Pinecone integrates seamlessly with various tools through its API. It's known for easy integration with OpenAI and Langchain, simplifying AI/LLM application development. Its serverless architecture further streamlines workflow integration. However, some users have noted limitations in its overall ecosystem integration compared to more established databases.
What the main competitors of Pinecone?
Top Pinecone competitors include Weaviate, Faiss, Milvus, and Vespa. These alternatives offer similar vector database capabilities for AI applications, focusing on efficient similarity search and scalability. They provide developers with tools to build AI-powered features like semantic search and recommendation systems.
Is Pinecone legit?
Pinecone is a legitimate and safe vector database specializing in AI applications. User reviews praise its speed, scalability, and ease of use, especially for similarity search and AI/ML tasks. However, some users mention limitations in ecosystem integration and pricing.
How much does Pinecone cost?
Pinecone pricing is not publicly available. Contact Pinecone directly to determine if Pinecone product pricing and plans meet your needs.
Is Pinecone customer service good?
Pinecone's customer support receives positive feedback, described as "incredible," "proactive," "smart," and "courteous." Users appreciate the helpful documentation and quick responses to inquiries. While their support bot may not always be as effective as alternatives, the human support team excels.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.