OrientDB 3.2 vs ArangoDB 3.10: A Comparative Analysis of Multi-Model Database Performance for Complex Data Structures

Introduction to Multi-Model Databases

When we started building our real-time analytics platform, we hit a wall with traditional relational databases. Our team discovered that handling complex, interconnected data structures was becoming a major bottleneck. That's when we turned to multi-model databases. After months of testing and benchmarking, I'm sharing our findings on OrientDB 3.2 vs ArangoDB 3.10.

The Problem with Relational Databases

Relational databases are great for structured data, but they fall short when dealing with complex, dynamic schemas. We were using MySQL, but as our dataset grew, query performance plummeted. We needed a database that could handle both document and graph data models efficiently.

Why OrientDB and ArangoDB?

We chose OrientDB and ArangoDB because they both support multiple data models - documents, graphs, and key-value pairs. This flexibility is crucial for our use case, where data structures are constantly evolving. Both databases have strong community support and are known for their scalability and performance.

Benchmarking Methodology

We used a combination of synthetic and real-world workloads to test the performance of both databases. Our test dataset consisted of 1 million documents, each with an average size of 1KB. We measured query performance, data ingestion rates, and memory usage under various loads.

Query Performance Comparison

Our tests showed that ArangoDB outperformed OrientDB in query performance, especially for complex graph queries. ArangoDB's AQL (ArangoDB Query Language) is more expressive and efficient than OrientDB's SQL-like query language. However, OrientDB's performance was more consistent across different workloads.

Data Ingestion Rates

OrientDB excelled in data ingestion rates, handling up to 10,000 documents per second. ArangoDB, on the other hand, topped out at around 5,000 documents per second. This is likely due to OrientDB's more efficient storage engine.

Memory Usage

ArangoDB used significantly more memory than OrientDB, especially under heavy loads. This is a concern for us, as we need to ensure our database can handle large datasets without running out of memory.

Conclusion

Choosing between OrientDB and ArangoDB depends on your specific use case. If query performance is your top priority, ArangoDB might be the better choice. However, if you need high data ingestion rates and efficient storage, OrientDB is worth considering. For our project, we decided to go with ArangoDB due to its superior query performance and flexibility.

Lessons Learned

Throughout this process, we learned that there's no one-size-fits-all solution for multi-model databases. It's essential to carefully evaluate your specific needs and benchmark different options before making a decision. We also realized that community support and documentation are crucial factors in the success of a database project.

Future Work

As we continue to scale our platform, we'll be exploring ways to optimize our database performance further. We're considering using a combination of both OrientDB and ArangoDB to leverage their respective strengths. Stay tuned for future updates on our database journey.