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Description
Cayley is an open-source database tailored for Linked Data, drawing inspiration from the graph database that supports Google's Knowledge Graph, previously known as Freebase. This graph database is crafted for user-friendliness and adept at handling intricate data structures, featuring an integrated query editor, a visualizer, and a Read-Eval-Print Loop (REPL). It supports various query languages, including Gizmo, which is influenced by Gremlin, a GraphQL-like query language, and MQL, a streamlined version catering to Freebase enthusiasts. Cayley's modular architecture allows seamless integration with preferred programming languages and backend storage solutions, making it production-ready, thoroughly tested, and utilized by numerous companies for their operational tasks. Additionally, it is optimized for application use, demonstrating impressive performance metrics; for instance, testing has shown that it can effortlessly manage 134 million quads in LevelDB on consumer-grade hardware from 2014, with multi-hop intersection queries—such as finding films featuring both X and Y—executing in about 150 milliseconds. By default, Cayley is set up to operate in-memory, which is what the backend memstore refers to, thereby enhancing its speed and efficiency for data retrieval and manipulation. Overall, Cayley offers a powerful solution for those looking to leverage linked data in their applications.
Description
Sparksee, which was previously referred to as DEX, optimizes both space and performance while maintaining a compact design that enables swift analysis of extensive networks. It supports a wide range of programming languages including .Net, C++, Python, Objective-C, and Java, making it versatile across various operating systems. The graph data is efficiently organized using bitmap data structures, achieving significant compression ratios. These bitmaps are divided into chunks that align with disk pages, enhancing input/output locality for better performance. By leveraging bitmaps, computations are executed using binary logic instructions that facilitate efficient processing in pipelined architectures. The system features complete native indexing, which ensures rapid access to all graph data structures. Node connections are also encoded as bitmaps, further reducing their storage footprint. Advanced I/O strategies are implemented to minimize the frequency of data pages being loaded into memory, ensuring optimal resource usage. Each unique value in the database is stored only once, effectively eliminating unnecessary redundancy, and contributing to overall efficiency. This combination of features makes Sparksee a powerful tool for handling large-scale graph data analyses.
API Access
Has API
API Access
Has API
Integrations
Docker
GraphQL
KeyLines
Kubernetes
ReGraph
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
Cayley
Website
github.com/cayleygraph/cayley
Vendor Details
Company Name
Sparsity Technologies
Founded
2010
Country
Spain
Website
sparsity-technologies.com