Aerospike and ScyllaDB are often evaluated side by side for latency-sensitive applications. Yet, the architectural decisions behind each database have direct implications for cost, availability, scalability, and operational complexity.
Aerospike defaults to RAM-resident primary indexes to optimize simple key/value workloads. ScyllaDB leverages modern NVMe storage, a shard-per-core architecture, and fast scaling with tablets to efficiently support richer data models and larger datasets.
If you’re evaluating databases for a low-latency use case, join us for a live session on how these two architectures compare. We’ll look at the tradeoffs behind each design decision and how to evaluate both databases on your own workloads.
We’ll cover:
- Different architectural approaches to low-latency databases
- Infrastructure efficiency and cost as datasets grow
- Scalability, resilience, and operational tradeoffs
- Access patterns and data models each database supports natively
- Tips for running fair and accurate benchmarks
