Impliance: A Next Generation Information Management Appliance
Bishwaranjan Bhattacharjee, Vuk Ercegovac, Joseph Glider, Richard, Golding, Guy Lohman, Volke Markl, Hamid Pirahesh, Jun Rao, Robert Rees,, Frederick Reiss, Eugene Shekita, Garret Swart

TL;DR
Impliance is a comprehensive, scalable, and easy-to-manage next-generation information management system designed to handle all data types and adapt to future data growth and complexity.
Contribution
It introduces a novel integrated hardware-software appliance that manages all data types uniformly, scales out efficiently, and simplifies operation through virtualization and automation.
Findings
Unified management of structured and unstructured data
Scales out using massive parallel processing
Simplifies management with virtualization
Abstract
ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from scratch, based upon today's requirements and hardware capabilities, would it look anything like today's database systems?" In this paper, we introduce Impliance, a next-generation information management system consisting of hardware and software components integrated to form an easy-to-administer appliance that can store, retrieve, and analyze all types of structured, semi-structured, and unstructured information. We first summarize the trends that will shape information management for the foreseeable future. Those trends imply three major requirements for Impliance: (1) to be able to store, manage, and uniformly query all data, not just structured…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Database Systems and Queries · Data Quality and Management · Scientific Computing and Data Management
