I am seeing a massive push from legacy database vendors introducing native document support and vector capabilities. Our team is discussing whether NoSQL losing popularity for enterprise applications is a real trend caused by these relational upgrades. If an RDBMS can handle semi-structured data patterns without losing rigid transactional safety, do we still need to deploy separate, highly distributed NoSQL clusters for modern corporate web apps?
3 answers
Relational databases adding document features is a marketing victory, but architectural reality is different. When you run multi-region, active-active web applications that require sub-millisecond write latencies globally, a relational engine with a JSON column will eventually fall over due to replication constraints. NoSQL engines are purpose-built for high availability and partition tolerance. Large enterprises continue to rely heavily on document stores because they decouple development teams from painful schema migrations during continuous deployment cycles.
Have you measured the exact indexing latency penalties when querying those complex JSON fields inside your relational setup compared to a native document database engine?
NoSQL remains dominant for unstructured data pools, but SQL has recaptured the standard business microservices layer due to improved handling of semi-structured objects.
Spot on. For basic CRUD operations with minor unstructured components, a modern RDBMS is perfectly adequate and saves you from managing multiple distinct data infrastructures.
We ran benchmarks last week and found that as the nesting depth of our unstructured data increased, the relational indexing overhead caused a 40% drop in read throughput compared to a native document store.