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Bringing Cloud-Native Storage to SAP IQ

Authors :
Muhammed Sharique
Mohammed Abouzour
Xi Deng
Ivan T. Bowman
John Smirnios
Güneş Aluç
Sagar Ranadive
Nandan Marathe
Source :
SIGMOD Conference
Publication Year :
2021
Publisher :
ACM, 2021.

Abstract

In this paper, we describe our journey of transforming SAP IQ into a relational database management system (RDBMS) that utilizes cheap, elastically scalable object stores on the cloud. SAP IQ is a three-decade old, disk-based, columnar RDBMS that is optimized for complex online analytical processing (OLAP) workloads. Traditionally, SAP IQ has been designed to operate on shared storage devices with strong consistency guarantees (e.g., high-caliber storage area network devices). Therefore, deploying SAP IQ on the cloud, as is, would have meant utilizing storage solutions such as NetApp or AWS EFS that provide a POSIX compliant file interface and strong consistency guarantees, but at a much higher monetary cost. These costs can accumulate easily to diminish the economies of scale that one would expect on the cloud, which can be undesirable. Instead, we have enhanced the design of SAP IQ to operate on cloud object stores such as AWS S3 and Azure Blob Storage. Object stores rely on a weaker consistency model, and potentially have higher latency; however, because of these design trade-offs, they are able to offer (i) better pricing, (ii) enhanced durability, (iii) improved elasticity, and (iv) higher throughput. By enhancing SAP IQ to operate under these design trade-offs, we have unlocked many of the opportunities offered by object stores. More specifically, we have extended SAP IQ's buffer manager and transaction manager, and have introduced a new caching layer that utilizes instance storage on AWS EC2. Experiments using the TPC-H benchmark demonstrate that we can gain an order of magnitude reduction in data-at rest storage costs while improving query and load performance.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 2021 International Conference on Management of Data
Accession number :
edsair.doi...........ba57d5f65ed39dede9fb47f4fb59ec30
Full Text :
https://doi.org/10.1145/3448016.3457563