Insights, tutorials, and updates from the Helix team
Enterprise needs go beyond features: you need security, compliance, reliability, and a clear path to ROI. These questions help you evaluate vendors with confidence and see where HelixDB fits.
Engineers and architects need clarity on developer experience, reliability, and scaling pathways without wading through vendor hype. Here is a concise checklist to guide your technical due diligence and see where HelixDB fits.
7 Essential Questions AI Product Managers Should Ask Before Choosing a Graph Vector Database Vendor
At HelixDB we've been focused on performance for the last few weeks. Here are our benchmarks for HelixDB, Neo4j, and Postgres (edges as joins) on a realistic graph dataset.
By developing directly on EC2, our engineers benchmark instantly on production-class hardware—no CI overhead, no local containers, no friction. Thanks to Coder, workspaces are fast, cost-efficient, and ready out of the box.
A quick and comprehensive guide on how to install HelixQL syntax highlighting on Cursor.
Schema migrations are one of the most important and usually poorly implemented features of a database. We've done it right from the start.
A complete guide to help you deploy Helix using Docker via the Helix CLI, allowing you to build and iterate faster.
A comprehensive guide to building a Graph-Vector RAG system in Python using HelixDB to recommend professors based on their research areas, leveraging both graph relationships and vector embeddings for intelligent search.
A comprehensive guide to get you started with HelixDB MCP endpoints for building agentic graph queries that evolve step-by-step without rebuilding from scratch.