As such, it can act as a drop-in replacement for existing IMDBs. Unlike buffer cache-based implementations, our tiering abstraction does not add any costs when reading data from DRAM. Leveraging information about access frequencies and patterns, our solution utilizes NVM's additional capacity while minimizing the associated access costs. We present a solution to this optimization problem. IMDBs thus need to navigate the trade-off between the two memory tiers. Yet, as NVM has a higher latency (5-15x) and a lower throughput (0.35x), it cannot fully replace DRAM. This new type of memory is persistent, has more capacity than DRAM (4x), and does not suffer from its density-inhibiting limitations. Non-volatile memory (NVM) addresses this challenge. However, as the DRAM technology approaches physical limits, scaling these databases becomes difficult. These in-memory databases (IMDBs) profit from DRAM's low latency and high throughput as well as from the removal of costly abstractions used in disk-based systems, such as the buffer cache. As a result, only 30% of the CPU cycles are used to retire instructions, and 70% of the CPU cycles are wasted to stalls for both traditional disk-based and new generation in-memory OLTP.Ī decade ago, it became feasible to store multi-terabyte databases in main memory. Even though ground-up designed in-memory systems can eliminate the instruction cache misses, the reduction in instruction stalls amplifies the impact of LLC data misses. The results show that, despite all the design changes, in-memory OLTP exhibits very similar micro-architectural behavior to disk-based OLTP: more than half of the execution time goes to memory stalls where instruction cache misses or the long-latency data misses from the last-level cache (LLC) are the dominant factors in the overall execution time. This paper sheds light on the micro-architectural behavior of in-memory database systems by analyzing and contrasting it to the behavior of disk-based systems when running OLTP workloads. In particular, we expect that in-memory systems exploit micro-architectural features such as instruction and data caches significantly better than disk-based systems. Hence, we expect significant differences in micro-architectural behavior when running OLTP on platforms optimized for in-memory processing as opposed to disk-based database systems. Furthermore, they usually adopt more lightweight concurrency control mechanisms, cache-conscious data structures, and cleaner codebases since they are usually designed from scratch. In-memory OLTP systems, on the other hand, process all the data in main-memory and, therefore, can omit the buffer pool. Results show that traditional OLTP systems mostly under-utilize the available micro-architectural resources. Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. The multi-node architecture was investigated for examining the performance overhead applying our algorithm. We evaluate the performance and abort rate of the single-node architecture where SSI is applicable. Our algorithm was integrated into two types of architecture as HTAP systems called as unified (single-node) or decoupled (multinode) storage architecture. Furthermore, we implemented the algorithm practically in an open-source database system that offers SSI. For serializability of HTAP systems, our model makes use of multiversion and allows more schedules with read operations whose corresponding write operations do not participate in the dependency cycles. We propose read safe snapshot (RSS) using multiversion CC (MVCC) theory and introduce the RSS construction algorithm utilizing serializable snapshot isolation (SSI). The aim of this study was serializability without additional aborts/waits. Furthermore, executing OLAP without affecting OLTP as much as possible is needed for HTAP systems. Although higher isolation level is ideal, considering OLAP read-only transactions in the context of OLTP scheduling achieving serializability forces aborts/waits and would be a potential performance problem. The OLAP side CC domain has been isolated from OLTP's CC and in many cases has been achieved by snapshot isolation (SI) to establish HTAP systems. Recently, hybrid transactional/analytical processing (HTAP) systems developed for executing OLTP and OLAP have attracted much attention. Concurrency Control (CC) ensuring consistency of updated data is an essential element of OLTP systems.
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