AsterixDB: A Scalable, Open Source BDMS
Abstract
AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data warehousing, social data storage and analysis, and other use cases related to Big Data. AsterixDB has a flexible NoSQL style data model; a query language that supports a wide range of queries; a scalable runtime; partitioned, LSM-based data storage and indexing (including B+-tree, R-tree, and text indexes); support for external as well as natively stored data; a rich set of built-in types; support for fuzzy, spatial, and temporal types and queries; a built-in notion of data feeds for ingestion of data; and transaction support akin to that of a NoSQL store. Development of AsterixDB began in 2009 and led to a mid-2013 initial open source release. This paper is the first complete description of the resulting open source AsterixDB system. Covered herein are the system's data model, its query language, and its software architecture. Also included are a summary of the current status of the project and a first glimpse into how AsterixDB performs when compared to alternative technologies, including a parallel relational DBMS, a popular NoSQL store, and a popular Hadoop-based SQL data analytics platform, for things that both technologies can do. Also included is a brief description of some initial trials that the system has undergone and the lessons learned (and plans laid) based on those early "customer" engagements.
Keywords
Cite
@article{arxiv.1407.0454,
title = {AsterixDB: A Scalable, Open Source BDMS},
author = {Sattam Alsubaiee and Yasser Altowim and Hotham Altwaijry and Alexander Behm and Vinayak Borkar and Yingyi Bu and Michael Carey and Inci Cetindil and Madhusudan Cheelangi and Khurram Faraaz and Eugenia Gabrielova and Raman Grover and Zachary Heilbron and Young-Seok Kim and Chen Li and Guangqiang Li and Ji Mahn Ok and Nicola Onose and Pouria Pirzadeh and Vassilis Tsotras and Rares Vernica and Jian Wen and Till Westmann},
journal= {arXiv preprint arXiv:1407.0454},
year = {2014}
}