For our log data aggregation and analysis platform, ScyllaDB offers unparalleled performance and scalability. Real-time processing of millions of log events per second has relied heavily on its capacity to manage high-throughput writes with incredibly low latency. We also value the low operational overhead—compared to other NoSQL databases, ScyllaDB uses less infrastructure because of its auto-tuning features and effective hardware utilization. In particular, the native support for time-based TTLs is useful for automatically controlling log retention. It just operates on a larger scale. Review collected by and hosted on G2.com.
ScyllaDB has a learning curve for teams used to Apache Cassandra or more traditional relational databases even if it boasts better performance. For some complex tuning parameters and architectural ideas, such log analytics, optimal performance for particular workloads depends on a better knowledge. Moreover, even if the documentation is usually good, some edge cases—especially those related to large-scale cluster management and repair activities—would benefit from more practical examples. The community and support network, however, are flexible which helps to close the distance. Review collected by and hosted on G2.com.
