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Description
*GraphDB allows the creation of large knowledge graphs by linking diverse data and indexing it for semantic search. *
GraphDB is a robust and efficient graph database that supports RDF and SPARQL.
The GraphDB database supports a highly accessible replication cluster. This has been demonstrated in a variety of enterprise use cases that required resilience for data loading and query answering. Visit the GraphDB product page for a quick overview and a link to download the latest releases.
GraphDB uses RDF4J to store and query data. It also supports a wide range of query languages (e.g. SPARQL and SeRQL), and RDF syntaxes such as RDF/XML and Turtle.
Description
Your organization's knowledge is scattered across various formats such as PDFs, spreadsheets, wikis, and ERP exports. Traditional retrieval augmented generation (RAG) techniques can only extract the top-K similar snippets, which is adequate for brief summaries but inadequate when precise and comprehensive answers are required.
Vedana adopts a structure-first methodology, allowing you to define your domain through anchors, attributes, and connections. It systematically ingests your data into a categorized knowledge graph, enabling AI agents to investigate it incrementally: performing graph queries, vector searches, and compiling answers from actual data. In this setup, the language model interprets the information while the data remains the authoritative source.
The advantages you gain include:
- Precise figures: obtaining specific prices, dates, and statuses directly from the graph
- Comprehensive outcomes: guaranteeing that all relevant records are included without omissions
- Multi-step reasoning: connecting product information to categories, regulations, and documents seamlessly
- Traceability: ensuring that every answer is linked back to specific nodes, edges, and data segments
- Consistency: delivering the same results with identical queries and processes
Additionally, the system comes with built-in evaluation using gold-standard datasets and is compatible with any language model. It can be deployed as open-core, managed cloud, or on-premises solutions, with pilot implementations available in just four weeks. This approach not only enhances accuracy but also fosters a deep understanding of the interconnected data landscape.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
Azure Marketplace
Yes
Gate
Yes
Hackolade
Yes
MongoDB
Yes
SolrCommerce
Yes
Integrations
Azure Marketplace
No
Gate
No
Hackolade
No
MongoDB
No
SolrCommerce
No
Pricing Details
Free, Standard and Enterprise versions available
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Ontotext
Founded
2008
Country
Bulgaria
Website
www.ontotext.com/product/graphdb
Vendor Details
Company Name
Epoch8
Founded
2017
Country
Georgia
Website
e8.team/
Product Features
Big Data
Collaboration
Yes
Data Blends
Yes
Data Cleansing
Yes
Data Mining
Yes
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
Yes
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Database
Backup and Recovery
Yes
Creation / Development
Yes
Data Migration
Yes
Data Replication
Yes
Data Search
Yes
Data Security
Yes
Database Conversion
Yes
Mobile Access
Yes
Monitoring
Yes
NOSQL
Yes
Performance Analysis
Yes
Queries
Yes
Relational Interface
Yes
Virtualization
Yes