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Loading...Introduction to Graph Databases for Real-Time Recommendations
When we decided to build a real-time recommendation engine for our e-commerce platform, we knew that traditional relational databases wouldn't cut it. Last quarter, our team discovered that graph databases were the way to go, but we were torn between TigerGraph 4.2 and Amazon Neptune 2.0. Here's what I learned when evaluating these two graph database giants for our specific use case.
The Problem with Traditional Databases
Traditional relational databases are great for transactions, but when it comes to complex, interconnected data, they fall short. We needed a database that could efficiently store and query graph structures - something that could handle billions of nodes and edges without breaking a sweat.
TigerGraph 4.2: The Powerhouse
TigerGraph 4.2 is an enterprise-grade graph database that boasts impressive performance and scalability. When I first tried to implement it, I was surprised by how easy it was to get started. The documentation is thorough, and the community support is top-notch.
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