In previous papers [SC05, SBC+07], some of us predicted the end of “one size fits all ” as a commercial relational DBMS paradigm. These papers presented reasons and experimental evidence that showed that the major RDBMS vendors can be outperformed by 1-2 orders of magnitude by specialized engines in the data warehouse, stream processing, text, and scientific database markets. Assuming that specialized engines dominate these markets over time, the current relational DBMS code lines will be left with the business data processing (OLTP) market and hybrid markets where more than one kind of capability is required. In this paper we show that current RDBMSs can be beaten by nearly two orders of magnitude in the OLTP market as well. The experimental evidence comes from comparing a new OLTP prototype, H-Store, which we have built at M.I.T. to a popular RDBMS on the standard transactional benchmark, TPC-C. We conclude that the current RDBMS code lines, while attempting to be a “one size fits all ” solution, in fact, excel at nothing. Hence, they are 25 year old legacy code lines that should be retired in favor of a collection of “from scratch ” specialized engines. The DBMS vendors (and the research community) should start with a clean sheet of paper and design systems for tomorrow’s requirements, not continue to push code lines and architectures designed for yesterday’s needs. 1.

Online Transaction Processing (OLTP) databases include a suite of features — disk-resident B-trees and heap files, locking-based concurrency control, support for multi-threading — that were optimized for computer technology of the late 1970’s. Advances in modern processors, memories, and networks mean that today’s computers are vastly different from those of 30 years ago, such that many OLTP databases will now fit in main memory, and most OLTP transactions can be processed in milliseconds or less. Yet database architecture has changed little. Based on this observation, we look at some interesting variants of conventional database systems that one might build that exploit recent hardware trends, and speculate on their performance through a detailed instruction-level breakdown of the major components involved in a transaction processing database system (Shore) running a subset of TPC-C. Rather than simply profiling Shore, we progressively modified it so that after every feature removal or optimization, we had a (faster) working system that fully ran our workload. Overall, we identify overheads and optimizations that explain a total difference of about a factor of 20x in raw performance. We also show that there is no single “high pole in the tent ” in modern (memory resident) database systems, but that substantial time is spent in logging, latching, locking, B-tree, and buffer management operations. Categories and Subject Descriptors H.2.4 [Database Management]: Systems — transaction processing; concurrency.

Replication is a widely used method for achieving high availability in database systems. Due to the nondeterminism inherent in traditional concurrency control schemes, however, special care must be taken to ensure that replicas don’t diverge. Log shipping, eager commit protocols, and lazy synchronization protocols are well-understood methods for safely replicating databases, but each comes with its own cost in availability, performance, or consistency. In this paper, we propose a distributed database system which combines a simple deadlock avoidance technique with concurrency control schemes that guarantee equivalence to a predetermined serial ordering of transactions. This effectively removes all nondeterminism from typical OLTP workloads, allowing active replication with no synchronization overhead whatsoever. Further, our system eliminates the requirement for two-phase commit for any kind of distributed transaction, even across multiple nodes within the same replica. By eschewing deadlock detection and twophase commit, our system under many workloads outperforms traditional systems that allow nondeterministic transaction reordering. 1.

Replicated systems are commonly used to provide highly available and fault tolerant applications, based on the use of replication and recovery protocols. Traditionally, the literature has focused on replicated systems which adopt the fail-stop failure model which presents good performance levels for replicated systems managing few state. This paper points out how the crash-recovery with partial amnesia failure model presents a better accuracy for replicated systems with huge state, but how its use has the amnesia phenomenon drawback. Then, the paper analyzes this phenomenon and how to deal with it in a basic configuration using a log-based recovery approach. Analyzing after, how it is supported and managed with other replication configurations. 1

Massively multiplayer online games (MMOs) have emerged as an exciting new class of applications for database technology. MMOs simulate long-lived, interactive virtual worlds, which proceed by applying updates in frames or ticks, typically at 30 or 60 Hz. In order to sustain the resulting high update rates of such games, game state is kept entirely in main memory by the game servers. Nevertheless, durability in MMOs is usually achieved by a standard DBMS implementing ARIES-style recovery. This architecture limits scalability, forcing MMO developers to either invest in high-end hardware or to over-partition their virtual worlds. In this paper, we evaluate the applicability of existing checkpoint recovery techniques developed for main-memory DBMS to MMO workloads. Our thorough experimental evaluation uses a detailed simulation model fed with update traces generated synthetically and from a prototype game server. Based on our results, we recommend MMO developers to adopt a copy-on-update scheme with a double-backup disk organization to checkpoint game state. This scheme outperforms alternatives in terms of the latency introduced in the game as well the time necessary to recover after a crash. 1.

Advances in hardware have enabled many long-running applications to execute entirely in main memory. As a result, these applications have increasingly turned to database techniques to ensure durability in the event of a crash. However, many of these applications, such as massively multiplayer online games and mainmemory OLTP systems, must sustain extremely high update rates – often hundreds of thousands of updates per second. Providing durability for these applications without introducing excessive overhead or latency spikes remains a challenge for application developers. In this paper, we take advantage of frequent points of consistency in many of these applications to develop novel checkpoint recovery algorithms that trade additional space in main memory for significantly lower overhead and latency. Compared to previous work, our new algorithms do not require any locking or bulk copies of the application state. Our experimental evaluation shows that one of our new algorithms attains nearly constant latency and reduces overhead by more than an order of magnitude for low to medium update rates. Additionally, in a heavily loaded main-memory transaction processing system, it still reduces overhead by more than a factor of two.

Due to its superiority such as low access latency, low energy consumption, light weight, and shock resistance, the success of flash memory as a storage alternative for mobile computing devices has been steadily expanded into personal computer and enterprise server markets with ever increasing capacity of its storage. However, since flash memory exhibits poor performance for small-to-moderate sized writes requested in a random order, existing database systems may not be able to take full advantage of flash memory without elaborate flash-aware data structures and algorithms. The objective of this work is to understand the applicability and potential impact that flash memory SSD (Solid State Drive) has for certain type of storage spaces of a database server where sequential writes and random reads are prevalent. We show empirically that up to more than an order of magnitude improvement can be achieved in transaction processing by replacing magnetic disk with flash memory SSD for transaction log, rollback segments, and temporary table spaces.

Massively Multiplayer Online Games (MMOs) are long-lived, interactive virtual worlds in which tens of thousands of people play together. In order to provide highly immersive experiences, MMO servers must support extremely high update rates – often hundreds of thousands of updates per second. A major concern for MMOs is to provide durability for the virtual world while limiting the overhead and perceived latency spikes introduced in the game. Recent work has shown that existing checkpoint-recovery algorithms developed for main memory DBMSs can be applied to MMO workloads but there is no single algorithm which outperforms all others over a wide range of update rates.. In this paper we propose two novel checkpointing algorithms that trade additional space in main memory for significantly lower latency. Compared to previous work, our new algorithms do not require any locking nor do they require bulk copies of the game state. Our experimental evaluation shows that our new algorithms attain nearly constant latency and achieve more than an order-of-magnitude lower overhead than the best previous methods. 1.