MongoDB vs Aerospike: Selecting the Right Database for GenAI Applications

MongoDB Atlas Vector Search and Aerospike Vector Search (AVS) are two prominent databases with vector search capabilities, essential features for AI applications such as recommendation engines, image retrieval, and semantic search. Both use the Hierarchical Navigable Small World (HNSW) algorithm for indexing and searching vector data. MongoDB Atlas Vector Search is great for applications that need a flexible data model and integration with regular queries, hybrid searches, and AI tools ecosystems. Aerospike Vector Search excels in high-performance, real-time scenarios where low latency and high throughput are key. The choice between MongoDB and Aerospike should be driven by application requirements, data complexity, performance needs, and scalability demands.