TigerGraph, provider of an ML and AI graph analytics platform, is releasing TigerGraph graph database v 3.9.3, introducing extended support for workload management, Kubernetes, and OpenCypher.
Developed in collaboration with TigerGraph customers, this latest release builds on TigerGraph’s existing enterprise readiness in the areas of fine-grained access control, activity monitoring, security, and data integrity, according to the company.
With these latest improvements, TigerGraph simplifies and expands resource management and data ingestion monitoring for applications like credit card fraud detection, where high volume, high speed, privacy, security, and overall system integrity are essential.
This release addresses a number of specific software system management needs of large enterprises:
- Workload management — Automatically assigns query tasks to the least-busy resources to maximize productivity
- Real-time data ingestion monitoring - Monitors the progress and integrity for high-speed data loading up to terabytes
- Support for Kubernetes — Enables simple, automated deployment and scaling of software components to meet dynamic needs, lowering operational costs
- Integrates OpenCypher — Adds a language familiar to many developers, to speed up creating and migrating graph queries, before leaning into GSQL for advanced and high-performance graph analytics
TigerGraph’s graph database helps businesses get more from their data—answers that are too inefficient for other databases to answer, better analytical insight, and more accurate machine learning.
With strong enterprise-readiness capabilities for access control, TigerGraph is the fastest and only scalable graph database for medium to large enterprises, according to the company.
This release will be available in November for both TigerGraph Cloud and as self-managed on-premises software.
For more information about these updates, visit www.tigergraph.com.