NoSQL Data Modeling Mistakes that Hurt Performance

Felipe Cardeneti Mendes' blog post delves into common NoSQL data modeling mistakes that can hinder performance, with a particular focus on ScyllaDB. The article explores various anti-patterns, such as large partitions, which can lead to high latency, and hot spots that result from uneven data access patterns. It also discusses the misuse of collections and low cardinality indexes, which can cause performance issues due to inefficient data storage and retrieval. Furthermore, the post addresses the complications introduced by tombstones in databases using Log-Structured Merge tree storage engines, highlighting the impact on read latency. Mendes provides insights on diagnosing these issues using ScyllaDB's monitoring tools and offers strategies like utilizing tracing and compaction strategies to mitigate these challenges. Additionally, the post promotes a free on-demand NoSQL Data Modeling Masterclass, which aims to enhance practitioners' understanding of optimizing NoSQL data models and avoiding performance pitfalls.