ScyllaDB was designed for efficiency, with the goal of delivering predictable low tail latency at scale. ScyllaDB’s close to the hardware design leverages a shard-per-core architecture and autotuning capabilities to maximize hardware utilization. This efficiency also translates to lower cost: less hardware is required to run similar workloads on ScyllaDB than with Cassandra or DynamoDB. Also, ScyllaDB runs anywhere; it’s available as a Database as a Service and can be deployed on any public cloud, or even on-premises. See NoSQL database comparisons and benchmarks.

ScyllaDB’s design includes a built-in efficient cache layer. This internal cache ensures predictable low latency for workloads at scale. For this reason, many teams have replaced caching layers (e.g., Redis, ElasticCache, DAX) with ScyllaDB. In DynamoDB cases, ScyllaDB can replace the underlying database (through its support of the DynamoDB-compatible API)  as well as replace the cache associated with it. ScyllaDB’s design helps reduce overall costs by making efficient use of infrastructure, as well as running anywhere. Why teams are replacing their external cache with ScyllaDB.

ScyllaDB is designed for low latency at scale, including flexible scaling to meet growing needs. Workloads that have thousands to millions of operations per second, as well as multiple terabytes or petabytes of data, will get the greatest benefits from ScyllaDB. ScyllaDB is designed for applications that work with semi-structured or structured data and query that data with known/predictable patterns. High cardinality with evenly distributed access patterns is also helpful. Is ScyllaDB a good fit.

ScyllaDB’s performance-focused design relies on its shard-per-core architecture, enabling efficient CPU utilization with a shared-nothing approach. Seastar, the framework ScyllaDB is built upon, allows for maximizing concurrency and reducing the latency of operations. ScyllaDB also bypasses OS-level memory management, performing direct I/O operations and leveraging its internal cache. Since ScyllaDB is written in C++, it reduces the complexity usually associated with tuning JVM parameters and avoids Java’s garbage collection pauses. What Makes ScyllaDB So Fast?

ScyllaDB is a NoSQL database designed for high performance, high throughput, and predictable low latency. Some of the tradeoffs are the lack of traditional relational database functionalities, such as arbitrary joins and ad-hoc querying. It does provide linearizable, single-partition transactions via lightweight transactions (Paxos) today—and Raft-based strong consistency for metadata (and soon for user tables)—but it does not yet support full ACID transactions spanning multiple partitions or tables. ScyllaDB also requires careful data modeling to ensure data is distributed according to its access patterns. On the other hand, its performance and scalability make it ideal for workloads that require predictable performance at scale. Read about database performance tradeoffs.

ScyllaDB distributes data using a shard-per-core architecture. It attributes partitions to CPU virtual cores for efficient parallelism and contention reduction. By leveraging consistent hashing for data distribution, it ensures the load is evenly distributed across the cluster and simplifies scalability. It replicates data across nodes distributed across multiple availability zones, which provides fault tolerance and high availability on the cloud. Additionally, ScyllaDB tablets allow rapid scaling of clusters in response to traffic spikes and increasing demand. ScyllaDB Architecture Overview.