Abstract
An elastic and highly available data store is a key component of many cloud applications. Existing data stores with strong consistency guarantees are designed and optimized for small updates, key-value access, and (if supported) small range queries over a predefined key column. This raises performance and availability problems for applications which inherently require large updates, non-key access, and large range queries. This paper presents a solution to these problems: Crescando/RB; a distributed, scan-based, main memory, relational data store (single table) with robust performance and high availability. The system addresses a real, large-scale industry use case: the Amadeus travel management system. This paper focuses on the distribution layer of Crescando/RB, the problem and theory behind it, the rationale underlying key design decisions, and the novel multicast protocol and replication framework it is composed of. Highlighting the key features of the distribution layer, we present experimental results showing that even under permanent node failures and large-scale data repartitioning, Crescando/RB remains fully available and capable of sustaining a heavy query and update load.
Highlights
The popularity of the cloud as a deployment platform and the extreme requirements of some enterprise and cloud applications have sparked a proliferation of so-called NoSQL systems
Over the last few years, several NoSQL systems have implemented strong consistency guarantees [8,24,39,60,66,68,77,78], targeting OLTP and Web workloads which traditionally relied on a standard relational database
We focus on the five areas most germane to the paper: NoSQL data stores, push-based query processing, scan-only query processing, state-machine replication, group communication
Summary
The popularity of the cloud as a deployment platform and the extreme requirements of some enterprise and cloud applications have sparked a proliferation of so-called NoSQL systems. As shown in a previous paper [74], Crescando is much less sensitive to the combination and selectivity of selection predicates than a conventional relational database This makes the engine especially suited for real-time business intelligence workloads such as our use case, where key-value stores are too restrictive in their consistency and/or data model, and relational databases lack the required performance, elasticity, availability, and robustness. Crescando/RB’s scan-only, two-stage execution model enables arbitrary, relational queries and updates, where key-value stores provide atomic access only for individual keys or (small) key ranges. We further show that even under node failures and large-scale repartitioning, the system remains available and can sustain a heavy read and write load
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
