Graph Technology

Use the full potential of graphs and transform your company. We will be happy to advise you! Contact us

What is a Graph Database?

A graph database is a specialized platform designed to store and manipulate data based on relationships. Unlike traditional relational databases, which rely on tables and rows, graph databases use a graph structure composed of three fundamental components:

  • Nodes: These represent entities (such as people, products, or locations) in your data.
  • Edges: They connect nodes and signify relationships between them.
  • Properties: They provide additional information about nodes and edges.

The magic lies in how these components interact:

Relationships First

In a graph database, relationships take centre stage. They connect the nodes to each other and, like nodes, can carry properties that can be used to filter queries. This flexibility allows for rich, interconnected data modelling.

Efficient Queries

Querying relationships is lightning fast because the edges belonging to a node are stored in linked lists. Whether you’re traversing social networks, supply chains, or recommendation engines, graph databases excel.

Visual Insights

Graphs are intuitive visual representations. They reveal patterns, dependencies, and hidden connections that other databases struggle to capture.

Graph Database vs. Relational Database: Key Differences

Technology Comparison
Relational DatabasesGraph Databases
Data ModelUse tables with fixed schemas requiring explicit relationships via primary and foreign keys.Structure data using nodes, edges, and properties allowing dynamic relationship representation.
OperationPrimarily suited for tabular data storage and complex joins.Optimize for traversing relationships efficiently.
ScalabilityScale horizontally but face challenges with complex queries.Scale effortlessly as data grows, maintaining performance.
PerformanceStruggle with deeply nested queries.Excel in querying interconnected data.
ComfortRequire predefined schemas and complex SQL.Embrace flexibility and adaptability.

Graph Database Modelling: Building the Foundation

Graph databases are more than just repositories for data; they are a dynamic representation of relationships. Our team excels in designing and implementing robust graph data models. Whether you’re migrating from a relational database or starting from scratch, we’ll create a schema that captures the intricate connections within your domain. Our services include:

  • Schema Design: Crafting efficient and expressive graph schemas tailored to your use case.
  • Data Migration: Seamlessly transitioning your data to a graph database.
  • Performance Optimization: Ensuring lightning-fast queries and traversals.

You can find more unique insights through graph databases in our recent blog post.

Graph Data Science: Extracting Insights from Relationships

Unlock the hidden gems in your data using graph algorithms and analytics. Our data scientists specialize in extracting meaningful patterns from interconnected data. Our offer:

  • Identify Key Players: Whether you want to identify bottlenecks in your supply chain, popular individuals in a social network or important parts in your bill of materials, centrality algorithms provide the answer for all these challenges.
  • Find hidden clusters: Social networks, customer segments or fraud rings - these are all examples of hidden clusters within your data. Community detection techniques reveal these groups, allowing you to tailor marketing strategies, detect anomalies, or enhance security.
  • Identify patterns: In Recommendation Engines, Protein Interaction Networks or Botnet Detection, entities with similar relationships and properties need to be identified. Similarity algorithms enable efficient data exploration and decision-making across diverse domains.

Generative AI with a Graph Database: Bridging Knowledge and Creativity

Imagine an AI that not only answers questions but generates contextually rich responses. Our approach combines a knowledge graph with generative AI models. Here’s how it works:

 

  • Grounded Responses: The AI understands your business-specific data by leveraging the knowledge graph. Responses are accurate, relevant, and explainable.
  • Vector Search: Implicit answers meet explicit facts. We seamlessly blend semantic meaning with factual accuracy by iterating through the graph providing context to the answer.
  • Data Governance: Control information flow, access, and governance within the graph.
Source: Neo4j 2023 (GenAI Stack Walkthrough: Build With Neo4j, LangChain & Ollama in Docker)
Source: Neo4j 2023 (GenAI Stack Walkthrough: Build With Neo4j, LangChain & Ollama in Docker)
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IBM Cloud Pak for Data Accelerator

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Data Governance

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Decision Optimization

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IBM Watson® Knowledge Catalog/Information Governance Catalog

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Operationalization of Data Science (MLOps)

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IBM Cloud Pak for Data – Test-Drive

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IBM Cloud Pak for Automation

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IBM Planning Analytics mit Watson

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IBM Watson Knowledge Studio

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IBM Cloud Pak for Data System

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IBM Watson Assistant

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Mastering digital transformation in insurance

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IBM Watson Discovery

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Digitalization and optimization in the manufacturing industr

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IBM Cognos Analytics 11

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Microsoft Power BI

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Analytics & Business Intelligence

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Data Vault Modeling Approach

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Analytics, BI & Planning

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FinOps Microsoft - Microsoft Cloud Cost Optimization

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FinOps Consulting

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IT Controlling – Determination and allocation of IT costs

We help to make IT controlling processes efficient and effective and to introduce suitable procedures for the internal allocation of IT costs.

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Managed service support for optimal license management

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Application Performance Monitoring Service

Application Performance Monitoring automates the IT monitoring of your applications, detects impending failures in advance and reduces manual activities to a minimum.

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IT Asset Management – Reducing Costs and Risks Sustainably

We help customers to increase the transparency of IT assets in use, identify potential savings for hardware and software, and avoid compliance risks at the same time.

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Application Performance Monitoring Service

Application Performance Monitoring automates the IT monitoring of your applications, detects impending failures in advance and reduces manual activities to a minimum.

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TIMETOACT provides support for ISO/IEC 19770-1 certification

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Effective claims management for insurers

Insurers have the challenge of helping people quickly and reliably in the event of a claim. At the same time, they have to keep the costs of claims and benefits management low so that insurance premiums remain affordable.

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Infrastructure Resource Management

Whether on-premise or in the cloud: With modern Infrastructure Resource Management, you provide your applications with the right amount of resources at all times.

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Infrastructure Resource Management

Whether on-premise or in the cloud: With modern Infrastructure Resource Management, you provide your applications with the right amount of resources at all times.

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IT Monitoring & Service Assurance Consulting

Ensure the continuous operation of your IT and enable customers and employees to use IT services and products without problems.

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Software analysis

We help to achieve transparency and clarity in legacy systems: technically, qualitatively and structurally.