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This paper introduces Mako, a highly available, high- throughput, and horizontally scalable transactional key-value store. Mako performs strongly consistent geo-replication to maintain availability despite entire datacenter failures, uses multi-core machines for fast serializable transaction process- ing, and shards data to scale out. To achieve these properties, especially to overcome the overheads of distributed transac- tions in geo-replicated settings, Mako decouples transaction execution and replication. This enables Mako to run transactions speculatively and very fast, and replicate transactions in the background to make them fault-tolerant. The key innovation in Mako is the use of two-phase commit (2PC) speculatively to allow distributed transactions to proceed without having to wait for their decisions to be replicated, while also preventing unbounded cascading aborts if shards fail prior to the end of replication. Our experimental evaluation on Azure shows that Mako processes 3.66M TPC-C transactions per second when data is split across 10 shards, each of which runs with 24 threads. This is an 8.6×higher throughput than state-of-the-art systems optimized for geo-replication. 

This paper introduces Mako, a highly available, highthroughput, and horizontally scalable transactional key-value store. Mako performs strongly consistent geo-replication to maintain availability despite entire datacenter failures, uses multi-core machines for fast serializable transaction processing, and shards data to scale out. To achieve these properties, especially to overcome the overheads of distributed transactions in geo-replicated settings, Mako decouples transaction execution and replication. This enables Mako to run transactions speculatively and very fast, and replicate transactions in the background to make them fault-tolerant. The key innovation in Mako is the use of two-phase commit (2PC) speculatively to allow distributed transactions to proceed without having to wait for their decisions to be replicated, while also preventing unbounded cascading aborts if shards fail prior to the end of replication. Our experimental evaluation on Azure shows that Mako processes 3.66M TPC-C transactions per second when data is split across 10 shards, each of which runs with 24 threads. This is an 8.6× higher throughput than state-of-the-art systems optimized for geo-replication. 

Quorum systems (e.g., replicated state machines) are critical distributed systems. Building correct, high-performance quorum systems is known to be hard. A major reason is that the protocols in quorum systems lead to non-deterministic state changes and complex branching conditions based on different events (e.g., timeouts). Traditionally, these systems are built with an asynchronous coding style with event-driven callbacks, but often lead to “callback hell” that makes code hard to follow and maintain. Converting to synchronous coding styles (e.g., using coroutines) is challenging because of the complex branching conditions. In this paper, we present Dependably Fast (DepFast), an effective, expressive framework for developing quorum systems. DepFast provides a unique QuorumEvent abstraction to enable building quorum systems in a synchronous style. It also supports composition of multiple events, e.g., timeouts, different quorums. To evaluate DepFast, we use it to implement two quorum systems, Raft and Copilot. We show that complex quorum systems implemented by DepFast are easy to write and have high performance. Specifically, it takes 25%–35% fewer lines of code to implement Raft and Copilot using DepFast, and the DepFast-based implementations have comparable performance with the state-of-the-art systems. 

Quorum systems (e.g., replicated state machines) are critical distributed systems. Building correct, high-performance quorum systems is known to be hard. A major reason is that the protocols in quorum systems lead to non-deterministic state changes and complex branching conditions based on different events (e.g., timeouts). Traditionally, these systems are built with an asynchronous coding style with event-driven callbacks, but often lead to “callback hell” that makes code hard to follow and maintain. Converting to synchronous coding styles (e.g., using coroutines) is challenging because of the complex branching conditions. In this paper, we present Dependably Fast (DepFast), an effective, expressive framework for developing quorum systems. DepFast provides a unique QuorumEvent abstraction to enable building quorum systems in a synchronous style. It also supports composition of multiple events, e.g., timeouts, different quorums. To evaluate DepFast, we use it to implement two quorum systems, Raft and Copilot. We show that complex quorum systems implemented by DepFast are easy to write and have high performance. Specifically, it takes 25%–35% fewer lines of code to implement Raft and Copilot using DepFast, and the DepFast-based implementations have comparable performance with the state-of-the-art systems. 

This paper presents Rolis, a new speedy and fault-tolerant replicated multi-core transactional database system. Rolis's aim is to mask the high cost of replication by ensuring that cores are always doing useful work and not waiting for each other or for other replicas. Rolis achieves this by not mixing the multi-core concurrency control with multi-machine replication, as is traditionally done by systems that use Paxos to replicate the transaction commit protocol. Instead, Rolis takes an "execute-replicate-replay" approach. Rolis first speculatively executes the transaction on the leader machine, and then replicates the per-thread transaction log to the followers using a novel protocol that leverages independent Paxos instances to avoid coordination, while still allowing followers to safely replay. The execution, replication, and replay are carefully designed to be scalable and have nearly zero coordination overhead across cores. Our evaluation shows that Rolis can achieve 1.03M TPS (transactions per second) on the TPC-C workload, using a 3-replica setup where each server has 32 cores. This throughput result is orders of magnitude higher than traditional software approaches we tested (e.g., 2PL), and is comparable to state-of-the-art, fault-tolerant, in-memory storage systems built using kernel bypass and advanced networking hardware, even though Rolis runs on commodity machines.