eBook
Five signs you’ve outgrown Couchbase
What you'll learn
If you're like many Couchbase users, you probably found it a solid initial choice for storing and querying JSON data. Its memory-first approach offers some performance benefits, and its mobile sync options provide early appeal. But as data volumes and transaction throughputs grow, that enthusiasm can fade fast, giving way to operational headaches, higher-than-expected costs, and performance issues that threaten your SLAs.
This eBook walks through five warning signs that your organization has outgrown Couchbase, from runaway scaling costs and latency spikes to limited multi-site replication and gaps in AI/ML support. If any of these resonate, it may be time to evaluate a database built to handle what comes next.
Key highlights
Couchbase's memory-first architecture can make scaling prohibitively expensive, driving sprawling server footprints and pricing you out of new revenue-generating applications
Latency spikes, write amplification, and unpredictable performance under load can make linear scalability impossible and put your brand reputation at risk
Lack of synchronous and asynchronous active-active replication makes it harder to span geographies and cloud zones with strong consistency
Couchbase's document-centric model limits its usefulness for AI/ML projects that require a single system optimized for real-time graph use cases
Cluster rebalancing disrupts application resilience and forces staff to spend excessive time managing large clusters just to meet baseline performance needs