KDB

Website: https://kdb.ai/

Category: Vector Database Engines

Tags: enterprise, scalable, vector-search, high-performance

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Description

KDB is a high-performance, scalable vector database designed for enterprise use, supporting billion-scale vector storage and retrieval. It is built to support production-grade AI applications with sub-100ms latency and high reliability.

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Features

• Hybrid Search: Supports combining semantic (dense) and keyword (sparse) vector searches in a single query for increased search relevance.
• Metadata Filtering: Allows filtering of vectors using structured metadata to refine search results.
• Temporal Similarity Search: Enables searching for similar patterns in time series data, supporting anomaly detection and multi-window queries.
• Multimodal Retrieval Augmented Generation (RAG): Handles unstructured data such as text, video, audio, and images for GenAI use cases.
• Multi-Index Search: Unifies multiple indexes for multi-layered embeddings, allowing flexible and faster search.
• On-Disk Indexing: Utilizes purpose-built qHNSW and qFlat indexing methods to reduce costs and memory requirements.
• Zero Embedding Search: Enables rapid search (up to 17x faster, using 12x less memory than HNSW) for fast-changing temporal data without the need for embeddings.
• Killer Compression: Provides up to 100x reduction in memory and storage for slow-changing, time-based datasets, and accelerates search by up to 10x.
• Dynamic Hybrid Search: Combines similarity, exact, and literal search in a single query, with results adapting to content changes.
• Integration with GenAI Tools: Compatible with LangChain, LlamaIndex, Vector-io, OpenAI, Azure AI, HuggingFace, and Unstructured.io.
• Production-Grade Performance: Delivers sub-100ms search latency and 99.99% uptime.
• Scalable: Supports billion-scale vector storage and retrieval for enterprise and large-scale applications.

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Pricing

• Free tier available: Build production-grade AI apps for free.
• Detailed paid plans are not specified in the provided content.

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Source

https://kdb.ai/