Non-Volatile RAM (NVRAM) is a novel class of hardware technology which is an interesting blend of two storage paradigms: byte-addressable DRAM and block-addressable storage (e.g. HDD/SSD). Most of the existing enterprise relational data management systems such as SAP HANA have their internal architecture based on the inherent assumption that memory is volatile and base their persistence on explicit handling of block-oriented storage devices. In this paper, we present the early adoption of Non-Volatile Memory within the SAP HANA Database, from the architectural and technical angles. We discuss our architectural choices, dive deeper into a few challenges of the NVRAM integration and their solutions, and share our experimental results. As we present our solutions for the NVRAM integration, we also give, as a basis, a detailed description of the relevant HANA internals.

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Modern applications employ key-value stores (KVS) in at least some point of their software stack, often as a caching system or a storage manager. Many of these applications also require a high degree of responsiveness and performance predictability. However, most KVS have similar design decisions which focus on improving throughput metrics, at times by sacrificing latency. While latency can be occasionally reduced by over provisioning hardware, this entails significant increase in costs. In this paper we present RStore, a KVS which focus on low tail latency as its primary goal, while also enabling efficient usage of hardware resources. To that aim, we argue in favor of techniques such as an asynchronous programming model, message-passing communication, and log-structured storage on modern hardware. Throughout the paper we discuss these and other design decisions of RStore that differ from those of more traditional systems. Our evaluation shows that RStore scales its throughput with an increasing number of cores while maintaining a robust behavior with low and predictable latency.

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