Don't know where to start? We can help!

By 2025, graph technologies will be used in 80% of data and analytics innovations facilitating rapid decision making across the enterprise (according to Gartner's "Market Guide for Graph Database Management Systems", Published 30 August 2022). Our clients ask how and where do I start this business innovation?

GraphPolaris' consultancy offer empowers organizations to harness the power of connected data and unlock valuable insights through efficient graph database solutions. With over 10 years of expertise in data modeling, graph data analytics and visualization, and system integration, we strive to help businesses leverage graph databases to drive innovation, make informed decisions, and gain a competitive edge in their respective industries.

We address the following challenges.

Graph Database Selection

Selecting a graph database poses the challenge of evaluating and comparing different graph database technologies based on factors such as performance, scalability, query language, ecosystem, and compatibility with existing infrastructure. It requires a thorough understanding of the specific use case requirements and careful consideration of trade-offs between features, community support, and long-term viability.

Data Modeling

One of the primary challenges is effectively modeling their data as a graph. Graph databases rely on relationships and connections between entities, and designing a robust graph data model requires a deep understanding of the underlying domain and data structures. We help our customers with identifying the appropriate nodes, relationships, and properties to represent their data accurately in a graph format.

Scalability and Performance

As the volume and complexity of data grow, ensuring scalability and maintaining optimal performance becomes crucial. Graph databases need to handle queries efficiently even as the graph expands, and customers oftentimes face challenges related to query optimization, indexing strategies, and managing large-scale graph data. We can provide architectural advice on scaling the database infrastructure to handle increased workloads and ensuring real-time responsiveness.

Integration with Existing Systems

Many customers already have established systems and databases in place, and integrating a graph database into their existing technology stack can be challenging. This includes data migration, ensuring data consistency between different databases, and enabling seamless data flow between graph databases and other systems. Integration challenges may also arise when connecting with data sources that do not inherently represent data in a graph format.

We deliver custom-tailored solutions.

Every project has its own challenges. By understanding these (domain) challenges and working with our graph database consultants, we can help you to effectively address questions centered around graph database adoption and machine learning, and ensure a smooth transition to graph database solutions.

Get in touch with us and find out how we can help! Mail a short description of your project vision to