Listing Thumbnail

    AllegroGraph Enterprise Edition

     Info
    Sold by: Franz Inc 
    Deployed on AWS
    AllegroGraph is a horizontally distributed, multi-modal Graph (RDF), Vector, and Document (JSON, JSON-LD) Knowledge Graph platform that includes SPARQL, Geospatial, Temporal, Social Networking, Text Analytics, and Large Language Model (LLM) capabilities for building Neuro-Symbolic AI applications. AllegroGraph features a built-in no-code visualization tool - Gruff and is the most secure Knowledge Graph platform on the market.
    5

    Overview

    Play video

    AllegroGraph: Enterprise Knowledge Graphs for Neuro-Symbolic and Agentic AI

    AllegroGraph is a distributed, multi-modal Graph, Vector, and Document database that provides the foundation for scalable Enterprise Knowledge Graphs, Neuro-Symbolic AI, and agentic AI applications. It combines RDF, SPARQL, vector search, document intelligence, rules, reasoning, geospatial, temporal, social network analytics, and enterprise-grade security in one ACID-compliant platform.

    GraphTalker extends AllegroGraph beyond traditional database interaction and simple natural-language query generation. It is a deeply integrated natural-language interface for AllegroGraph that enables users to ask questions, explore relationships, and gain insight from enterprise Knowledge Graphs without writing SPARQL manually. Integrated in a manner similar to Gruff, GraphTalker can be launched directly from WebView and connected to a selected repository. GraphTalker is designed for agentic exploration. Rather than translating a question into a single query, it can inspect repository structure, examine schema and ontology patterns, generate and test queries, observe results, refine its approach, and return grounded answers. This makes AllegroGraph more accessible to business users and more productive for data scientists, KG developers, and application teams.

    GraphTalker can also be integrated directly into end-user applications through APIs, allowing organizations to embed natural-language KG interaction into dashboards, portals, workflows, analytics tools, and AI-powered systems.

    Industry-Leading Security AllegroGraph security is designed to protect sensitive data in complex graph, vector, and document environments. Its Triple Attribute Security model applies controls directly to data elements, including triples, annotations, embeddings, and text fragments. This makes AllegroGraph well suited for healthcare, financial services, policing, intelligence, and government. The same framework applies across Knowledge Graph, vector, document, and GraphTalker workflows, giving organizations granular control without sacrificing performance.

    Retrieval-Augmented Generation for Trusted AI AllegroGraph supports Retrieval-Augmented Generation (GraphRAG) by grounding LLM responses in trusted enterprise Knowledge Graphs. Instead of relying only on model memory or unstructured text retrieval, AllegroGraph provides semantic context, relationships, rules, provenance, and governed access to enterprise data.

    Natural-Language Queries and Reasoning GraphTalker enables users to ask questions in plain language while working with AllegroGraph to understand repository structure, determine the right query strategy, and return reliable results. This is valuable when users do not already know the schema, ontology, or available relationships.

    Enterprise Document Deep Insight AllegroGraph's VectorStore capabilities connect enterprise documents with Knowledge Graphs, allowing organizations to query documents, text fragments, and graph relationships together. This helps transform previously inaccessible dark data into governed enterprise knowledge.

    Symbolic Rules and Explainable AI AllegroGraph includes built-in rule-based capabilities for symbolic reasoning. Organizations can encode business logic, infer new relationships, support classification, and produce more explainable outcomes based on enterprise knowledge.

    Ontology, Taxonomy, and Semantic Model Development AllegroGraph streamlines the creation and refinement of ontologies, taxonomies, and semantic models. LLM-assisted workflows and GraphTalker's natural-language interaction help users explore concepts, relationships, hierarchies, and classifications more efficiently.

    Enhanced Scalability and Performance AllegroGraph supports large-scale enterprise Knowledge Graph deployments through FedShard and high-availability architecture. These capabilities help distribute workloads, manage large repositories, improve query performance, and scale KG applications.

    Modern Web Interface and Visualization AllegroGraph provides a modern WebView experience for managing repositories, launching tools, and interacting with the platform. GraphTalker is deeply integrated into this experience, while Gruff provides advanced Knowledge Graph visualization for exploring RDF graphs, relationships, annotations, provenance, temporal context, scores, weights, and semantic structures.

    Summary AllegroGraph is more than a graph database. It is a governed semantic platform for building explainable, trustworthy, and enterprise-ready AI applications. By combining Knowledge Graphs, vector search, document intelligence, symbolic reasoning, enterprise security, scalability, visualization, and GraphTalker's agentic natural-language interface, AllegroGraph provides a semantic foundation for Neuro-Symbolic and Agentic AI.

    Highlights

    • Horizontally distributed Graph, Vector, and Document database for highly scalable Knowledge Graph and Neuro-Symbolic AI Solutions.
    • AllegroGraph is 100 percent ACID, supporting Transactions: Commit, Rollback, and Checkpointing along with Multi-Master Replication for high availability requirements.
    • AllegroGraph supports SHACL, SPARQL 1.1, RDFS++, OWL2-RL, and Prolog rules and reasoning from numerous client applications as well as visualizations from Graph industry's leading browser - Gruff.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    AmazonLinux 2023

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    Features and programs

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    AllegroGraph Enterprise Edition

     Info
    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (41)

     Info
    Dimension
    Cost/hour
    m5a.2xlarge
    Recommended
    $4.40
    c5a.24xlarge
    $52.80
    x1e.32xlarge
    $70.40
    x1e.xlarge
    $2.20
    c5.18xlarge
    $35.20
    m5a.8xlarge
    $17.60
    c5a.16xlarge
    $35.20
    c5.12xlarge
    $26.40
    c5.9xlarge
    $17.60
    c5.24xlarge
    $52.80

    Vendor refund policy

    30 days

    How can we make this page better?

    Tell us how we can improve this page, or report an issue with this product.
    Tell us how we can improve this page, or report an issue with this product.

    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

     Info

    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Additional details

    Usage instructions

    Once the instance is running, SSH into it using the username 'ec2-user' and provide your Amazon private key. Run 'cat README' to find the autogenerated password for the AllegroGraph 'admin' account. Visit http://<your-public-ip>:10035 in your browser to access AllegroGraph WebView. Log in as 'admin', using the password you found in the README file. AllegroGraph is now ready to use via browser, command line (via agtool), or various client libraries. Consult the AllegroGraph Quick Start guide at https://franz.com/agraph/support/documentation/current/agraph-quick-start.html#tutorial-dir  for examples of how to create a repository and load it with sample data.

    Resources

    Vendor resources

    Support

    Vendor support

    Please allow 24 hours

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

    Product comparison

     Info
    Updated weekly

    Accolades

     Info
    Top
    100
    In Analytic Platforms
    Top
    50
    In Data Warehouses
    Top
    10
    In Databases & Analytics Platforms

    Customer reviews

     Info
    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
    Functionality
    Ease of use
    Customer service
    Cost effectiveness
    1 reviews
    Insufficient data
    Insufficient data
    Insufficient data
    Insufficient data
    0 reviews
    Insufficient data
    Insufficient data
    Insufficient data
    Insufficient data
    Positive reviews
    Mixed reviews
    Negative reviews

    Overview

     Info
    AI generated from product descriptions
    Distributed Database Architecture
    Horizontally distributed multi-modal Graph, Vector, and Document database supporting large-scale enterprise Knowledge Graph deployments with FedShard and high-availability architecture.
    Query and Reasoning Languages
    Support for SPARQL 1.1, SHACL, RDFS++, OWL2-RL, and Prolog rules enabling semantic queries, symbolic reasoning, and inference capabilities across knowledge graphs.
    Data Security Model
    Triple Attribute Security model applying granular controls directly to data elements including triples, annotations, embeddings, and text fragments with ACID compliance and multi-master replication.
    Natural Language Interface
    GraphTalker agentic natural-language interface enabling repository exploration, schema inspection, query generation and refinement without manual SPARQL writing, with API integration capabilities.
    Vector and Document Integration
    VectorStore capabilities connecting enterprise documents with Knowledge Graphs, enabling combined querying of text fragments, embeddings, and graph relationships for Retrieval-Augmented Generation workflows.
    Knowledge Graph Database Engine
    Virtuoso 08.03.3334-pthreads DBMS with SPARQL and SQL query processing capabilities for knowledge graph interactions
    Conversational AI Integration
    OpenLink AI Layer (OPAL) enabling conversational interaction with DBpedia and support for RAG/GraphRAG processing pipelines with AI Agents and Assistants
    Data Query and Transformation
    SPARQL Query Processor, R2RML Processor, and Data Transformation Middleware Layer for semantic data processing and conversion
    Search and Discovery Capabilities
    Faceted Search and Browsing functionality with HTML-based Admin Interface for knowledge graph exploration and management
    Authentication and Security
    Virtuoso Authentication Layer (VAL) providing secure access control and authentication mechanisms for the knowledge graph instance
    Vector Database Capabilities
    Elasticsearch functions as a vector database with extensive GenAI integrations, providing unified access to ML models, connectors, and frameworks through API calls for semantic search and RAG applications.
    Observability and Monitoring
    Full-stack observability solution with OpenTelemetry native integration supporting 400+ integrations including AWS services like Bedrock, CloudWatch, CloudTrail, EC2, Firehose, and S3 for comprehensive visibility across environments.
    AI-Driven Security Analytics
    Security operations platform powered by Search AI Platform delivering AI-driven security analytics for SIEM, endpoint security, and cyber security with advanced automation features for attack surface analysis.
    Serverless Architecture
    Serverless deployment option built on Search AI Lake architecture combining vast storage, compute, low-latency querying, and advanced AI capabilities without infrastructure management requirements.
    Enterprise-Grade Data Management
    Unified data management across multiple sources with enterprise-grade security, flexible provisioning options across serverless, cloud, and on-premises infrastructure deployments.

    Security credentials

     Info
    Validated by AWS Marketplace
    FedRAMP
    GDPR
    HIPAA
    ISO/IEC 27001
    PCI DSS
    SOC 2 Type 2
    No security profile
    No security profile
    -
    -
    -
    -
    -

    Contract

     Info
    Standard contract
    No
    No

    Customer reviews

    Ratings and reviews

     Info
    5
    1 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    100%
    0%
    0%
    0%
    0%
    1 AWS reviews
    reviewer2784384

    Unified customer graphs have improved order insights and support better decision making

    Reviewed on Dec 05, 2025
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for AllegroGraph  is to build a customer graph with relationships to depict all the information related to orders.

    An example of how I use AllegroGraph  for customer graph relationships is that we utilized it to view all the information in one comprehensive graph.

    What is most valuable?

    The best feature AllegroGraph offers is the user interface.

    I use the simple user interface to view all the information together in one large graph.

    AllegroGraph has positively impacted my organization as we have made significant steps forward to consolidate all information into one comprehensive knowledge graph.

    These steps help with decision making.

    What needs improvement?

    AllegroGraph is perfect and has room for improvement.

    For how long have I used the solution?

    I have been using AllegroGraph for one year.

    What do I think about the stability of the solution?

    AllegroGraph is stable.

    What do I think about the scalability of the solution?

    AllegroGraph's scalability is good.

    How are customer service and support?

    I did not interact with the customer support team.

    How would you rate customer service and support?

    Which solution did I use previously and why did I switch?

    I did not previously use a different solution before AllegroGraph.

    What's my experience with pricing, setup cost, and licensing?

    My experience with pricing, setup cost, and licensing was straightforward with no problems.

    Which other solutions did I evaluate?

    Before choosing AllegroGraph, I did not evaluate other options.

    What other advice do I have?

    My advice for others looking into using AllegroGraph is that the best way to use the product is to experiment with all the features that the product offers immediately. I gave this product a rating of 10.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    View all reviews