Home / Companies / Memgraph / Blog / Post Details
Content Deep Dive

From Edge Vector Indexing to LLM Models: What’s New in Memgraph 3.4

Blog post from Memgraph

Post Details
Company
Date Published
Author
Sabika Tasneem
Word Count
689
Company Posts That Month
5
Language
English
Hacker News Points
-
Post removed?
No
Summary

Memgraph 3.4.0 introduces several new features and performance enhancements to improve the experience with graph databases, particularly in leveraging large language models (LLMs). Key updates include smarter vector indexing that now supports edges, allowing for similarity searches on relationships, and memory optimization through quantization. The release also enhances monitoring for replica recovery processes, introduces a non-blocking index creation process to minimize database locking, and updates GraphQL compatibility for better integration. MAGE 3.4.0 brings new utilities for text and date manipulation and node merging, while Memgraph Lab 3.4.0 offers improved graph layouts, expanded Graph Chat LLM options, and enhanced security with PKCE for OAuth2 authentication. These updates aim to provide more control, flexibility, and efficiency in building intelligent, context-aware applications using Memgraph.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
LLM 6 4,152 612 181 +19%
Vector Search 4 1,836 305 108 +20%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.