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With the growth of cloud computing, distributed databases, and now AI/ML, the role of graph databases has evolved to include more operational workloads. These workloads introduce greater requirements on graph databases, including scaling to terabytes and beyond, low-latency transactions, high data throughput, enterprise-grade availability, and disaster recovery.

This guide will help guide you to make an informed decision about which approach to graph databases best suits your requirements. Download this guide to learn:

• The key criteria to consider when selecting a graph database
• How analytical vs. transactional use cases make a difference
• Some of the vendors in this space that you should consider