A Survey on Array Storage, Query Languages, and Systems

TL;DR

This survey comprehensively reviews array data storage, query languages, and systems, highlighting past developments, current practices, and future research directions in array processing for Big Data.

Contribution

It provides the first unified overview of array storage, query languages, and systems, consolidating research and identifying gaps in array data processing.

Findings

Analyzes array partitioning and storage techniques.

Reviews array query language proposals and foundations.

Surveys existing array processing systems.

Abstract

Since scientific investigation is one of the most important providers of massive amounts of ordered data, there is a renewed interest in array data processing in the context of Big Data. To the best of our knowledge, a unified resource that summarizes and analyzes array processing research over its long existence is currently missing. In this survey, we provide a guide for past, present, and future research in array processing. The survey is organized along three main topics. Array storage discusses all the aspects related to array partitioning into chunks. The identification of a reduced set of array operators to form the foundation for an array query language is analyzed across multiple such proposals. Lastly, we survey real systems for array processing. The result is a thorough survey on array data storage and processing that should be consulted by anyone interested in this research topic, independent of experience level. The survey is not complete though. We greatly appreciate pointers towards any work we might have forgotten to mention.