What is TopK?
TopK is a cloud-native database specifically designed to streamline and enhance search functionalities within your applications. If you're building systems that rely on robust search – whether it's semantic search, Retrieval-Augmented Generation (RAG), multi-modal search, or personalized recommendations – TopK provides a unified solution that simplifies your workflow and boosts performance. It combines text, vector, and metadata filtering into a single, efficient database, all at a competitive price point.
Key Features:
🔎 Unified Search API: Execute text, vector, and metadata searches with a single API call. This simplifies integration and allows you to power any type of retrieval with minimal code.
🗄️ Flexible Data Storage: Store and manage your documents and collections efficiently. TopK handles the complexities of indexing and retrieval, letting you focus on application logic.
⚡ High-Performance Vector Search: Perform vector searches on both dense and sparse vectors, with native support for scalar and binary quantization to optimize performance and storage.
📝 Built-in Keyword Search: Utilize BM25 scoring for traditional keyword searches on indexed text documents, providing a familiar and reliable search method.
⚙️ Hybrid Retrieval: Combine multi-vector and text retrieval to achieve the most relevant search results. This hybrid approach leverages the strengths of both methods.
📊 Advanced Filtering: Apply precise filters to your searches, ensuring you retrieve only the data that meets your specific criteria. This enhances relevance and reduces noise.
🌐 Production Scale Ready: Scale to Billions of Documents without breaking a sweat, with 99.9+% availability in multiple regions.
Use Cases:
Retrieval-Augmented Generation (RAG): Enhance your large language models (LLMs) by providing them with relevant context retrieved from TopK. For example, you can use TopK to find relevant documents or knowledge base entries to improve the accuracy and factual grounding of your LLM's responses.
Semantic Search Engine: Build a search engine that understands the meaning behind user queries, not just the keywords. TopK's vector search capabilities allow you to find documents that are semantically similar to the query, even if they don't contain the exact same words.
Multi-modal Search: Combine text, image, audio, and video data in a single index. A user could search for "red sports car," and TopK could return relevant images, videos, and text descriptions, all ranked by their overall similarity to the query.
Recommendation Engine: TopK can be used to create a recommendation engine. By storing user preferences and item characteristics as vectors, TopK can quickly find items that are similar to those a user has liked in the past.
Conclusion:
TopK offers a powerful and efficient solution for developers building search-intensive applications. Its unified API, hybrid retrieval capabilities, and focus on performance make it an ideal choice for a wide range of use cases, from RAG and semantic search to multi-modal search and recommendations. TopK's commitment to developer experience, competitive pricing, and enterprise-grade security (SOC2 and HIPAA compliance) further solidify its position as a leading search database solution.
More information on TopK
Launched
2024-11
Pricing Model
Free Trial
Starting Price
Global Rank
Follow
Month Visit
<5k
Tech used
Framer,Google Fonts,Gzip,HTTP/3,OpenGraph,HSTS
TopK was manually vetted by our editorial team and was first featured on September 4th 2025.
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