Question: I'm looking for a scalable Knowledge Graph platform that can integrate with multiple data sources and provide real-time analytics.

If you need a Knowledge Graph platform that can scale to accommodate many data sources and that offers real-time analytics, Neo4j is a good choice. It includes tools for data science and machine learning, vector search and analytics, and is used for knowledge graphs, intelligent applications and real-time insights. Neo4j offers graph-native scale, flexibility and enterprise-grade security, and can be deployed self-hosted, cloud-managed or as a fully managed service.

Another contender is Franz's AllegroGraph, a high-performance, horizontally scalable graph database that also can store large language models (LLMs) and vector storage. It's geared for industries like health care, intelligence and financial analysis. Franz also offers Gruff, a visual interface for exploring and querying knowledge graphs, and has worked with many Fortune 500 companies to build Enterprise Knowledge Graphs.

For a developer-focused option, Grafbase is an option. It lets developers assemble multiple data sources into a single graph that can be deployed at the edge or on-premise. Grafbase supports modern tooling for building and deploying GraphQL APIs, federation and advanced security, so it can be used to integrate with a wide variety of tools and services.

Last, Lettria is a no-code AI platform that marries large language models with symbolic AI, letting people extract insights from text data and build their own NLP models for tasks like ontology enrichment and text-to-graph conversions. With an interface that's designed to be easy to use and strong data security, Lettria can be deployed on private or public clouds, and it's designed to keep data private and secure.