This paper studies the design of a key-value (KV) store that can take full advantage of modern storage hardware with built-in transparent compression capability. Many modern storage appliances/drives implement hardware-based data compression, transparent to OS and applications. Moreover, the growing deployment of hardware-based compression in Cloud infrastructure leads to the imminent arrival of Cloud-based storage hardware with built-in transparent compression. By decoupling the logical storage space utilization efficiency from the true physical storage usage, transparent compression allows data management software to purposely waste logical storage space in return for simpler data structures and algorithms, leading to lower implementation complexity and higher performance. This work proposes a table-less hash-based KV store, where the basic idea is to hash the key space directly onto the logical storage space without using a hash table at all. With a substantially simplified data structure, this approach is subject to significant logical storage space under-utilization, which can be seamlessly mitigated by storage hardware with transparent compression. This paper presents the basic KV store architecture, and develops mathematical formulations to assist its configuration and analysis. We implemented such a KV store KallaxDB and carried out experiments on a commercial SSD with built-in transparent compression. The results show that, while consuming very little memory resource, it compares favorably with the other modern KV stores in terms of throughput, latency, and CPU usage.

This paper studies utilizing the growing family of solid-state drives (SSDs) with built-in transparent compression to simplify the data structure of cache design. Such storage hardware allows the user applications to intentionally under-utilize logical storage space (i.e., sparse LBA utilization, and sparse storage block content) without sacrificing the physical storage space. Accordingly, this work proposed an index-less cache management approach to largely simplify the flash-based cache management by leveraging SSDs with built-in transparent compression. We carried out various experiments to evaluate the write amplification and read performance of the proposed cache management, and the results show that our proposed indexless cache management can achieve comparable or much better performance than the conventional policies while consuming much less host computing and memory resources.

This paper presents an approach to enable relational database take full advantage of modern storage hardware with built-in transparent compression. Advanced storage appliances (e.g., all-flash array) and some latest SSDs (solid-state drives) can perform hardware-based data compression, transparently from OS and applications. Moreover, the growing deployment of hardware-based compression capability in Cloud storage infrastructure leads to the imminent arrival of cloud-based storage hardware with built-in transparent compression. To make relational database better leverage modern storage hardware, we propose to deploy a dual in-memory vs. on-storage page format: While pages in database cache memory retain the conventional row-based format, each page on storage devices has a column-based format so that it can be better compressed by storage hardware. We present design techniques that can further improve the on-storage page data compressibility through additional light-weight column data transformation. We the impact of compression algorithms on the selection of column data transformation techniques. We integrated the design techniques into MySQL/InnoDB by adding only about 600 lines of code, and ran Sysbench OLTP workloads on a commercial SSD with built-in transparent compression. The results show that the proposed solution can bring up to 45% additional reduction on the storage cost at only a few percentage of performance degradation.

This thesis advocates a novel DRAM-only strategy to reduce the computing system memory cost for the first time, and investigates its applications to database systems. This thesis envisions a low-cost DRAM module called block-protected DRAM, which reduces bit cost by significantly relaxing the DRAM raw reliability and meanwhile employs long error correction code (ECC) to ensure data integrity at small coding redundancy. Built upon the exactly same DRAM technology, today's byte-accessible DRAM and envisioned block-protected DRAM strike at different trade-offs between memory bit cost and native data access granularity, and naturally form a heterogeneous DRAM-only memory system. The practical feasibility of such heterogeneous memory systems is further strengthened by the new media-agnostic and latency-oblivious CPU-memory interfaces such as IBM's OpenCAPI/OMI and Intel's CXL. This DRAM-only design approach perfectly leverages the existing DRAM manufacturing infrastructure and is not subject to any fundamental technology risk and uncertainty. Hence, before NVM technologies could eventually fulfill their long-awaited promises (i.e., DRAM-grade speed at flash-grade cost), this DRAM-only design framework can fill the gap to empower continuous progress and advances of computing systems. This thesis aims to develop techniques that enable relational and NoSQL databases to take full advantage of the envisioned low-cost heterogeneous DRAM system. As the first step, we studied how one could employ heterogeneous DRAM to implement a low-cost tiered caching solution for relational database, and obtained encouraging results using MySQL as a test vehicle.