A knowledge graph is a structured representation of real-world entities and the relationships between them. It effectively captures the context and meaning of data by connecting objects, events, situations, or concepts through well-defined relationships. This interconnected structure enables deeper understanding and reasoning across various domains. The growing demand for artificial intelligence (AI) and generative AI technologies is a key driver of the knowledge graph market. As organizations seek to harness data for strategic advantage, they are increasingly adopting advanced AI tools to enhance decision-making and boost operational efficiency. In this landscape, knowledge graphs play a pivotal role by providing a robust foundation of structured knowledge that AI systems can leverage.

Additionally, the acceleration of digital transformation—fueled in part by the global pandemic—has pushed organizations to embrace adaptive AI technologies to meet evolving customer expectations and market demands. The synergy between knowledge graphs and generative AI is poised to drive substantial market growth, as more businesses recognize their potential to enhance customer experiences and operational performance.

Key Developments

1) Memgraph 3.0 Launch

In February 2025, Memgraph declared the release of version 3.0 of its open-source in-memory graph database, marking a significant advancement in the knowledge graph landscape. This release introduced cutting-edge features such as GraphRAG (Retrieval-Augmented Generation in Graph) and native vector search support. These capabilities enable real-time, secure, and context-aware Generative AI applications—including enterprise chatbots, assistants, and intelligent agents.

2) TrustGraph and Memgraph Integration

In December 2024, a strategic move to scale enterprise knowledge retrieval, TrustGraph integrated Memgraph to convert unstructured data into structured knowledge graphs. This integration empowers AI systems to navigate and extract insights from complex vertical datasets such as aerospace and legal tech. These developments signal a rapid evolution in the knowledge graph space, where graph-native RAG, vector search, and real-time graph querying are becoming essential to building secure, scalable, and accurate Generative AI solutions.

Startups in the Market

Memgraph

Memgraph is a high-performance graph database company established in 2016, focused on real-time data processing and analytics. The company helps organizations unlock the potential of graph data structures to manage complex relationships and rapidly changing environments. Memgraph’s flagship platform is optimized for handling high-throughput transactions, making it ideal for mission-critical use cases that demand fast, actionable insights from connected data. It supports multiple data ingestion methods, including real-time streaming from platforms like Kafka, allowing users to build in-memory dynamic graphs with ease. Designed for both performance and usability, Memgraph serves industries such as finance, cybersecurity, and telecommunications. The company continues to innovate through active community involvement and ongoing development of features that enhance user experience and operational efficiency.

Datavid

Datavid is a data consultancy firm dedicated to helping organizations unlock the full potential of both structured and unstructured data. Founded in 2018 by Balvinder Dang, the company was established in response to the growing demand for expert support in data migration and management, especially during transitions to cloud and hybrid infrastructures.

GraphBase

GraphBase is a technology company specializing in advanced graph database solutions with a focus on large-scale knowledge graphs. Serving a wide range of industries, GraphBase provides powerful tools to manage and analyze complex datasets, helping organizations uncover meaningful connections and insights across diverse data sources. The company’s platform is designed for seamless integration with machine learning models, including Large Language Models (LLMs), enhancing data processing and enabling more intelligent, context-aware applications.