Durable Distributed Cache Architecture

The world runs on transactional database systems. Every business depends on them, and users interact with them many times each day. Unfortunately, most of today’s transactional systems are still build on top of traditional relational database systems, which lack the scale-out design capabilities necessary to take full advantage of modern datacenter architectures.

Today’s database vendors have applied three common design patterns around traditional systems to extend them into distributed scale-out database systems. These approaches – Shared-Disk, Shared-Nothing and Synchronous Commit - overcome some of the limitations of single-server deployments, but remain complex and prone to error.

By stepping back and rethinking database design from the ground up, Jim Starkey, NuoDB’s technical founder, has come up with an entirely new design approach called Durable Distributed Cache (DDC). The net effect is a system that scales-out/in dynamically on commodity machines and virtual machines, has no single point of failure, and delivers full ACID transactional semantics.

Memory-Centric vs. Storage-Centric

All general-purpose relational databases to date have been architected around a storage-centric assumption. Unfortunately this creates a fundamental problem relative to scaling out. In effect, these database systems are fancy file systems that arrange for concurrent read/write access to disk-based files such that users do not interfere with each other.

The NuoDB DDC architecture inverts this idea, imagining the database as a set of in-memory container objects that can overflow to disk if necessary and can be retained in backing stores for durability purposes.

All servers in the NuoDB DDC architecture can request and supply objects (referred to as Atoms) thereby acting as peers to each other. Some servers have a subset of the objects at any given time, and can therefore only supply a subset of the database to other servers. Other servers have all the objects and can supply any of them, but will be slower to supply objects that are not resident in memory.

NuoDB consists of two types of servers: Transaction Engines (TEs) hold a subset of the objects; Storage Managers (SMs) are servers that have a complete copy of all objects. TEs are pure in memory servers that do not need use disks. They are autonomous and can unilaterally load and eject objects from memory according to their needs. Unlike TEs, SMs can’t just drop objects on the floor when they are finished with them; instead they must ensure that they are safely placed in durable storage.

For those familiar with caching architectures, you might have already recognized that these TEs are in effect a distributed DRAM cache, and the SMs are specialized TEs that ensure durability. Hence the name Durable Distributed Cache.

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