CONTACT US
Overview: What Is GraphAware Hume?
GraphAware Hume is a graph-based intelligence analysis platform built around powerful knowledge graph capabilities at the core. Its purpose is to to break down data silos and empower analysts with a unified view of intelligence, streamlining complex data analysis.
The power of graph technologies used throughout its software stack, from the Neo4j database to visualization, makes it much easier to ingest, process, query, analyze, and visualize your data as networks of interconnected entities, delivering advanced analytical capabilities to your organization. In this article, we discuss why Hume is such a strong performer in its class by exploring its unique capabilities and advantages.
What Is GraphAware Hume?
As mentioned earlier, GraphAware Hume is a government-grade data analytics platform unlocking the value of graph databases for fast and intuitive intelligence analysis. With no-code and low-code approaches, its capabilities significantly reduce the time to value in any graph project, whether you're using an analytics application or some other interactive application that uses connected graph data.
GraphAware Hume delivers powerful knowledge graph capabilities, elegantly enabling both structured and unstructured data use cases in a secured fashion. That includes all aspects of the Graph AppDev lifecycle, including graph-centric ETL ingestion and manipulation data workflows using a friendly, drag-and-drop interface, or workflows for advanced graph data science pipelines. It also includes powerful and customizable graph-based alerting and visual graph analysis along with geospatial and temporal analysis. Read more to explore Graphaware Hume capabilities in depth.
Why Do We Need Graph Databases and GraphAware Hume?
Graph databases themselves are just now successfully beginning to exit the "Gartner Hype Cycle for Data Management 2022" report for data management. It has advanced to the famous "Slope of Enlightenment" and is on its way to the "Plateau of Productivity". In all likelihood, it will eventually make its way off of this report and into a more permanent future "Gartner Graph Magic Quadrant" in the coming years.
As a new commercial offering within the last decade, many questions are left swirling in this space. People are only gradually beginning to understand graph databases, including the various permutations (e.g. native vs multi-model, LPG vs RDF etc), what the databases do and what surrounding software is available. At the same time, very few CIOs of any Fortune 500 company do not have a well-funded, core transformation initiative around knowledge graphs.
All technical business leaders are aware they need to start using graphs, graph databases and graph data science to compete in the coming decades — whether that means harvesting and leveraging large-scale unstructured data, creating a digital twin of their business, targeting fraud at scale or creating more effective recommendation engines that can scale.
Simultaneously, there's a lack of skilled and knowledgable resources in the market, little tooling to enable it and limited understanding about where and how to get started. However, even Google has cited how critical graphs / network science will be to the future of data science.
Leading Graph Offerings
The graph market is still very much emerging. But given the intensity of interest around graphs from all quarters, there are now hundreds if not thousands of new startups and even later-stage companies in the space. Below are the four main categories of graph offerings:
graph databases
- Neo4j
- Virtuoso
- ArangoDB
- OrientDB
- Microsoft CosmosDB
- Amazon Neptune
- GraphDB
- JanusGraph
- TigerGraph
- DGraph
graph Visualization tools
- Keylines
- Linkurious
- Kineviz
- Tom Sawyer Perspectives
- SemSpect
- Graphlytic
- yWorks
- Graphistry
- Gephi
- Bloom
Graph Enablement Platforms
- GraphAware Hume
- Microsoft Graph
Graph-powered Applications
- Data.world
- DiffBot
- Katana
- RelationalAI
- Stardog
- Limbik
- OctaveBio
Principal GraphAware Hume Features
1. Knowledge graph platform. Knowledge graphs are more than applications on graph databases. By their very name, they imply something much deeper, including a context for new knowledge we can surface from the world of structured and unstructured data. GraphAware’s Hume platform takes this concept to the next level with its cutting-edge features that streamline every aspect of the knowledge graph lifecycle. Hume enables organizations to effortlessly integrate disparate data sources, enrich data with advanced AI-driven annotations, and uncover hidden relationships using powerful visualization tools. Its robust query capabilities allow users to perform complex analyses and surface actionable insights, while the platform’s intuitive UI ensures accessibility for both technical and non-technical users. In a day when most CIOs don't know where to begin with managing data, the comprehensive Hume platform makes creating, managing and analyzing your knowledge graph in record time a reality.
2. Powerful graph analytics. Hume provides the deepest graph visualization layer available today, far beyond the simple force-directed viz that's typically associated with graph analysis to date. Fully interactive, it's made for the proactive surfacing of data, patterns and trends that are nearly impossible to identify any other way, even at massive scale. Its advanced features include a variety of layout algorithms that allow users to choose the most effective representation for their data, as well as the ability to create custom visualizations tailored to specific use cases. The Visual Query Builder feature allows you to ask complex, multi-hop questions in seconds by simply describing patterns and filtering by attributes—even without knowing exactly what you’re looking for or having any knowledge of graph query language.
3. Advanced geospatial and temporal analysis. High-quality geospatial analysis has long been a missing piece in the graph technology landscape. Similarly, temporal analysis has remained a significant challenge due to the complexity and scale of time-based data within a graph context.With both the included capabilities in GraphAware Hume and the easy extensibility of the platform, you can Narrow down your search geospatially and/or temporally, using the map view and the time bar. Interpret the results of your investigation by plotting them on the map or replaying events as they occurred.
4. Enterprise ETL / orchestration. Truly elegant and highly effective, the low-code / no-code, drag-and-drop ETL UI has changed the game in the graph space. Hume Orchestra feature offers read and write capabilities in all directions, making it a versatile tool for your data needs. It simplifies the process of designing and configuring data ingestion and maniputlation workflows for both streaming and batch data processing capabilities. Hume Orchestra is particularly well-suited for real-time scenarios with large data volumes, enabling parallel processing and complex flows with multiple sources and targets. It excels in sourcing and data cleaning for graph applications, ensuring your data is ready for analysis and use.
5. Connector library. As part of the orchestration capability, the library of connectors is a common-sense collection that just keeps growing. It facilitates seamless integration of internal and external services into data enrichment pipelines. Connector library supports connections with pre-existing and third-party microservices, as well as custom integrations using REST APIs, JSON, and other methods. This functionality enables secure API calls to services such as face recognition, language translation, or OSINT data providers, effectively leveraging existing investments.
6. Graph data science. GraphAware Hume supports advanced graph data science (GDS) algorithms for identifying influential nodes, link prediction, and community detection to discover clusters within networks. The capabilities are tailor-designed to manage and optimise time-consuming tasks on large graphs.
7. Actions. Imagine a business user being able to apply a Louvain community-detection algorithm in a guided way through a pre-defined Hume Action right in their graph UI. With GraphAware Hume Actions, analysts can execute complex or repetitive queries during intelligence analysis with just one click. These actions can also be easily shared with their team, boosting collaboration and efficiency. This is the power of Hume Actions.
8. Alerting. GraphAware Hume provides enterprise alerting based on thresholds, patterns and algorithmic outcomes, enabling organizations to stay on top of their data with automatic detection of emerging patterns of interest. Notifications are delivered within seconds of new information entering the system, ensuring timely responses to critical insights. With a graph-centric approach, users can receive alerts through various channels, including the UI, email, SMS text, and more. An intuitive interface simplifies the configuration, monitoring, and management of alerts and notifications, making it easy to customize and oversee your alerting needs.
9. Action Board Views. Action Boards are a flexible visualisation tool for analysts to create advanced composite views of intelligence from connected data.
Build detailed intelligence summaries, such as dashboards, 360-degree entity profiles, and suspect nomination lists. Views can be tailored for the analysis of an individual entity, or a group of entities.
Top Advantages of Hume (GraphAware)
- Thought-leading architecture. GraphAware Hume is architected by some of the most well-known names in the graph space, including Alessandro Negro, author of the Manning book "Graph-Powered Machine Learning". The platform is way ahead of other attempts at similar capabilities because the team creating it are some of the most prominent thought leaders in the emerging space.
- Low-code / no-code graph AppDev. GraphAware Hume's first advantage is radically reducing time to value. Prior to Hume, tasks such as ETL, leveraging LLMs, enriching, alerting and taking action required a lot of code. If you wanted to perform analyses or build an application, even more code. Hume reduces all that, driving value out of your graph data much faster.
- Comprehensive platform. While there are many emerging tools out there, a significant portion of them are one off or not production ready. That means you must proliferate tools far more than you would otherwise need to. GraphAware Hume offers all the most important capabilities for graph analytics and AppDev in a single extensible platform.
- Enterprise-grade security. Not surprisingly, graph database and Hume itself have been used early on in highly sensitive and secured environments across defense, intelligence and law enforcement. As a result, the Hume platform has rock-solid, enterprise-ready security from the top down.
- Neo4j aligned. While the Neo4j graph database is not the only option, it's easily the most enterprise ready. The GraphAware team and the Hume platform are uniquely aligned with Neo4j at present, making the capabilities that empower Neo4j unusually well suited and performant.
When to use GraphAware Hume
What is GraphAware Hume used for? While GraphAware Hume can be used for a wide variety of use cases with Neo4j, its unique value becomes evident when it comes to graph AppDev and advanced intelligence analysis. Some of the most common uses cases include:
Check out our GraphAware Hume Resources for specific examples on how Hume can be leveraged.
GraphAware Hume Customers
GraphAware has many customers, from well-known commercial brands to intelligence and law enforcement. It has a strong and growing presence worldwide and is used by a variety of organizations, including the Global top-ten banks, and renown defense and intelligence agencies in US, Australia and EU.
References:
- Gartner Predicts Exponential Growth of Graph Technology
- High Tech Security Firm Limbik Uses Hume to Create Information Defense System
- What Is a Knowledge Graph? Powering Business With Graphs
- Natural Language is Structured Data
- What is the Order of Steps in Natural Language Understanding? 7 Step Guide
- The Exceptional Value of Graph Embeddings
- How to Use Hume Node
- Top Ten Reasons To Consider Neo4j
- Beginner Overview of Neo4j
