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    AllegroGraph Enterprise Edition

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    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.
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    Overview

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    AllegroGraph provides the foundational structure for scalable Enterprise Knowledge Graphs for building Neuro-Symbolic AI applications. AllegroGraph is a multi-modal Graph, Vector, and Document database that is fully ACID compliant.

    Industry Leading Security - AllegroGraph's security is designed to protect the most sensitive data within the flexible environment of a graph/document database. This innovative feature within AllegroGraph provides the necessary power and flexibility to address high-security data environments such as HIPAA access controls, privacy rules for banks, and security models for policing, intelligence and government. In addition, AllegroGraph Triple Attribute Security is easier to use and provides more expressiveness than security methods in relational databases or property graph databases, while avoiding performance degradation.

    Retrieval Augmented Generation (RAG) for LLMs - AllegroGraph 8.0 guides Generative AI content through RAG, feeding LLMs with the 'source of truth.' This innovative approach helps avoid 'hallucinations' by grounding the output in fact-based knowledge. As a result, organizations can confidently apply these insights to critical decision-making processes, secure in the knowledge that the information is both reliable and trustworthy.

    Natural Language Queries and Reasoning - The new LLMagic functions within AllegroGraph 8.0 serve as the bridge between human language and machine understanding, offering a dynamic natural language interface for both querying and reasoning processes. Users can now engage with AllegroGraph 8.0 in a manner that closely mirrors human conversation, making AI capabilities accessible to a broader set of users and increasing productivity for current users.

    Enterprise Document Deep-insight - New VectorStore capabilities within AllegroGraph 8.0 offer a seamless bridge between enterprise documents and Knowledge Graphs. This unique feature empowers users to access a wealth of knowledge hidden within documents, allowing users to query content that was previously considered 'dark data.' Users gain a comprehensive view of enterprise data, contributing to the business's deeper insights from its proprietary data. One unique feature of AllegroGraph's vector store implementation is that it lives under the same security framework that we apply to the graphs. AllegroGraph's 'triple-attributes' mechanism puts security 'in' the data elements itself. AllegroGraph offers the ability to annotate individual triples or text fragments and thus provides the most granular access method of any Graph-Vector platform.

    AI Symbolic Rule Generation - AllegroGraph offers built-in rule-based system capabilities tailored for symbolic reasoning. This unique feature distills complex data into actionable, interpretable rules. AI symbolic rule generation enables predictions or classifications based on data and provides transparent explanations for their decisions by expressing them in symbolic rules, enhancing trust and interpretability in AI systems.

    Streamlined Ontology and Taxonomy Creation - LLMagic can streamline the complex and often labor-intensive task of crafting ontologies and taxonomies for any topic. By analyzing diverse data, and identifying patterns, relationships, and semantic connections that underpin the subject matter, LLMagic can quickly generate structured hierarchies and classifications that form the foundation of ontologies and taxonomies. Users can more quickly create ontologies and taxonomies with a reduced need for manual intervention, accelerating the knowledge organization process and enhancing the quality and comprehensiveness of the created structures.

    Enhanced Scalability and Performance - AllegroGraph 8.0 includes enhanced FedShard™ capabilities making the management of sharding more straightforward and user-friendly while reducing query response time and improving overall system performance.

    New Web Interface - AllegroGraph 8.0 includes a striking redesign of its web interface - AGWebView. This fresh look and feel provides users an enhanced and intuitive way to interact with the platform, while co-existing in parallel with the Classic View.

    Advanced Knowledge Graph Visualization - A new version of Franz's industry-leading graph visualization software, Gruff v9, is integrated into AllegroGraph 8.0. Gruff v9 is the only graph visualization tool that illustrates RDF-Star (RDF*) annotations, enabling users to add descriptions to edges in a graph - such as scores, weights, temporal aspects and provenance.

    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
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    Pricing

    AllegroGraph Enterprise Edition

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    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)

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    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

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    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) .

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    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

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    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

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    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.

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    Overview

     Info
    AI generated from product descriptions
    Multi-Modal Database Architecture
    Horizontally distributed database supporting Graph (RDF), Vector, and Document (JSON, JSON-LD) data types for scalable Knowledge Graph and Neuro-Symbolic AI applications.
    Query and Reasoning Languages
    Support for SPARQL 1.1, SHACL, RDFS++, OWL2-RL, and Prolog rules enabling comprehensive querying and reasoning capabilities across knowledge graphs.
    Granular Data Security Framework
    Triple Attribute Security mechanism providing row-level access controls at individual triple and text fragment level, with security annotations embedded within data elements themselves.
    Retrieval Augmented Generation for LLMs
    RAG capabilities that ground Large Language Model outputs in fact-based knowledge graphs to reduce hallucinations and ensure reliable information for critical decision-making.
    Graph Visualization with RDF-Star Support
    Integrated Gruff v9 visualization tool capable of illustrating RDF-Star annotations on graph edges, including scores, weights, temporal aspects, and provenance information.
    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

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

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    Standard contract
    No
    No

    Customer reviews

    Ratings and reviews

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    1 ratings
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    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?

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