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Loading...Introduction to Multi-Model Databases
When dealing with complex, real-time data processing applications, choosing the right database can be a daunting task. Last quarter, our team discovered that our existing relational database was struggling to keep up with the demands of our application. We needed a database that could handle multiple data models, including document, graph, and key-value stores. This led us to explore multi-model databases. In this article, I'll share our experience benchmarking ArangoDB 3.10, OrientDB 3.2, and Cosmos DB.
The Problem with Traditional Databases
Traditional databases are designed to handle specific types of data and use cases. Relational databases are great for transactional data, but they can become cumbersome when dealing with large amounts of unstructured or semi-structured data. NoSQL databases, on the other hand, offer more flexibility but often lack the consistency and durability of relational databases. Multi-model databases aim to bridge this gap by supporting multiple data models within a single database.
ArangoDB 3.
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