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Description
JanusGraph stands out as a highly scalable graph database designed for efficiently storing and querying extensive graphs that can comprise hundreds of billions of vertices and edges, all managed across a cluster of multiple machines. This project, which operates under The Linux Foundation, boasts contributions from notable organizations such as Expero, Google, GRAKN.AI, Hortonworks, IBM, and Amazon. It offers both elastic and linear scalability to accommodate an expanding data set and user community. Key features include robust data distribution and replication methods to enhance performance and ensure fault tolerance. Additionally, JanusGraph supports multi-datacenter high availability and provides hot backups for data security. All these capabilities are available without any associated costs, eliminating the necessity for purchasing commercial licenses, as it is entirely open source and governed by the Apache 2 license. Furthermore, JanusGraph functions as a transactional database capable of handling thousands of simultaneous users performing complex graph traversals in real time. It ensures support for both ACID properties and eventual consistency, catering to various operational needs. Beyond online transactional processing (OLTP), JanusGraph also facilitates global graph analytics (OLAP) through its integration with Apache Spark, making it a versatile tool for data analysis and visualization. This combination of features makes JanusGraph a powerful choice for organizations looking to leverage graph data effectively.
Description
Streamlined distributed computing significantly enhances graph-analytics performance without requiring extensive infrastructure changes. By incorporating a broader variety of data for standardization and visualization on the graph, insights can be significantly strengthened. The combination of advancements in both graph and deep learning results in efficiencies that facilitate prompt insights on the largest graphs in existence. Katana Graph equips Financial Services firms with the tools to tap into the vast possibilities offered by graph analytics and AI at scale, enabling everything from real-time fraud detection to comprehensive customer insights. Leveraging breakthroughs in high-performance parallel computing (HPC), Katana Graph’s intelligent platform evaluates risks and uncovers customer insights from massive data sets using rapid analytics and AI capabilities that surpass those of alternative graph technologies. This transformative approach allows organizations to stay ahead of trends and make data-driven decisions with confidence.
API Access
Has API
API Access
Has API
Integrations
Apache Atlas
Apache Cassandra
Apache HBase
Apache Solr
Apache Spark
Elasticsearch
G.V() Gremlin IDE
Google Cloud Bigtable
Graphlytic
Hackolade
Integrations
Apache Atlas
Apache Cassandra
Apache HBase
Apache Solr
Apache Spark
Elasticsearch
G.V() Gremlin IDE
Google Cloud Bigtable
Graphlytic
Hackolade
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
JanusGraph
Founded
2016
Country
United States
Website
janusgraph.org
Vendor Details
Company Name
Katana Graph
Founded
2020
Country
United States
Website
katanagraph.com
Product Features
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
