ScyllaDB V brings new performance, resilience, and ecosystem advantages that resolve longstanding challenges of legacy NoSQL databases.ScyllaDB V is Here
Our latest enterprise release, ScyllaDB Enterprise 2022.2 is a production-ready release providing stability and performance improvements introduced in ScyllaDB Open Source 5.1 and building upon the abundance of enhancements in ScyllaDB Enterprise 2022.
This release supports Time-to-Live (TTL) expirations of data in our DynamoDB-compatible API, known as “Alternator.” The TTL has a deletion delay of up to 48 hours. With ScyllaDB’s Alternator, you can set a custom deletion delay (by default set to 24 hours). Also, Alternator will BYPASS CACHE for scans employed in TTL expiration, reducing the impact on user workloads. We’ve also implemented new metrics to observe TTL expirations.
It is now possible to limit read rates and writes rates into a partition with a new WITH per_partition_rate_limit clause for the CREATE TABLE and ALTER TABLE statements. This is useful to prevent hot-partition problems when high rate reads or writes are bogus (for example, arriving from spam bots).
This feature extends nodetool refresh to allow loading arbitrary SSTables that do not belong to a particular node into the cluster. It loads the SSTables from disk, calculates the data’s owning nodes, and automatically streams the data to the owning nodes. In particular this is useful when restoring a cluster from backup.
So-called “ghost rows” manifest when rows in a materialized view do not correspond to any base table rows. Such inconsistencies should be prevented altogether and ScyllaDB strives to avoid them, but if they happen, the new PRUNE MATERIALIZED VIEW statement can be used to restore a materialized view to a fully consistent state without rebuilding it from scratch.
In ordinary (asynchronous) materialized views the operation returns before the view is updated. In synchronous materialized views the operation does not return until the view is updated. This enhances consistency but reduces availability as in some situations all nodes might be required to be functional.
ScyllaDB now supports AWS EC2 I4i series instances. Capitalizing on 3rd generation Intel Xeon “Ice Lake” processors, the AWS Nitro System hypervisor, and low-latency Nitro NVMe SSDs, ScyllaDB can achieve more than twice the throughput and lower latencies with I4i servers versus comparable i3 servers.
ScyllaDB Enterprise also supports systems with Arm-based processors, including the new AWS Im4gn and Is4gen storage-optimized instances powered by Graviton2 processors. Now compiled to run on any AArch64 architecture, you can even run ScyllaDB in a Docker container on an Arm-based M1-powered Macintosh for next-gen application development.
Integrated via a Seastar update, a new I/O scheduler seeks to find what is known as the effective dispatch rate — the fastest rate at which the system can process data without running into internal queuing jams to keep latency low.
The same data transfer logic used for repair, a background process to sync data between nodes, is now used for topology changes. Node operations can restart from points where stopped without re-sending synced data, a significant time-saver when adding or removing large nodes. New off-strategy compaction can also be utilized to optimize performance.
Enabling migration to ScyllaDB with potentially no application code changes, Alternator has been updated with valuable new support for:
Guardrails are a collection of reservations that make it harder to use non-recommended options in production, such as:
ScyllaDB administrators can use default settings or customize guardrails as needed.
After more than 6,000 commits originating from five open source releases, ScyllaDB Enterprise 2022 has many additional features and enhancements since ScyllaDB Enterprise 2021, including:
ScyllaDB Enterprise builds on the proven features and capabilities of ScyllaDB Open Source, while also bringing with a set of unique enterprise-only features.
Learn how to configure ScyllaDB to replace or extend Amazon DynamoDB.
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