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Description
FalkorDB is an exceptionally rapid, multi-tenant graph database that is finely tuned for GraphRAG, ensuring accurate and relevant AI/ML outcomes while minimizing hallucinations and boosting efficiency. By utilizing sparse matrix representations alongside linear algebra, it adeptly processes intricate, interconnected datasets in real-time, leading to a reduction in hallucinations and an increase in the precision of responses generated by large language models. The database is compatible with the OpenCypher query language, enhanced by proprietary features that facilitate expressive and efficient graph data querying. Additionally, it incorporates built-in vector indexing and full-text search functions, which allow for intricate search operations and similarity assessments within a unified database framework. FalkorDB's architecture is designed to support multiple graphs, permitting the existence of several isolated graphs within a single instance, which enhances both security and performance for different tenants. Furthermore, it guarantees high availability through live replication, ensuring that data remains perpetually accessible, even in high-demand scenarios. This combination of features positions FalkorDB as a robust solution for organizations seeking to manage complex graph data effectively.
Description
Designed specifically for handling super large-scale graphs with latency measured in milliseconds, this graph database continues to engage with the community for its preparation, promotion, and popularization. Nebula Graph ensures that access is secured through role-based access control, allowing only authenticated users. The database supports various types of storage engines and its query language is adaptable, enabling the integration of new algorithms. By providing low latency for both read and write operations, Nebula Graph maintains high throughput, effectively simplifying even the most intricate data sets. Its shared-nothing distributed architecture allows for linear scalability, making it an efficient choice for expanding businesses. The SQL-like query language is not only user-friendly but also sufficiently robust to address complex business requirements. With features like horizontal scalability and a snapshot capability, Nebula Graph assures high availability, even during failures. Notably, major internet companies such as JD, Meituan, and Xiaohongshu have successfully implemented Nebula Graph in their production environments, showcasing its reliability and performance in real-world applications. This widespread adoption highlights the database's effectiveness in meeting the demands of large-scale data management.
API Access
Has API
API Access
Has API
Integrations
Docker
Amazon Web Services (AWS)
ChatGPT
Cognee
DSPy
Gemini
Google Cloud Platform
LangChain
Llama
Mem0
Integrations
Docker
Amazon Web Services (AWS)
ChatGPT
Cognee
DSPy
Gemini
Google Cloud Platform
LangChain
Llama
Mem0
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
FalkorDB
Founded
2023
Country
Israel
Website
www.falkordb.com
Vendor Details
Company Name
vesoft
Founded
2018
Country
China
Website
nebula-graph.io