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Kevin Porter

dblp:358/1772 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 50% Distributed and cloud data management · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 62% Storage systems · 19% Cloud and datacenter computing · 19%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management
data replication
0.712023
Techniques and Efficiencies from Building a Real-Time DBMS · Proc. VLDB Endow. 2023
Database system architecture and tuning
real-time database
0.712023
Techniques and Efficiencies from Building a Real-Time DBMS · Proc. VLDB Endow. 2023
Distributed systems
consensus
0.712023
Techniques and Efficiencies from Building a Real-Time DBMS · Proc. VLDB Endow. 2023
Cloud and datacenter computing
cloud deployment
0.212023
Techniques and Efficiencies from Building a Real-Time DBMS · Proc. VLDB Endow. 2023
Storage systems
flash and SSD
0.212023
Techniques and Efficiencies from Building a Real-Time DBMS · Proc. VLDB Endow. 2023
YearPublicationVenuePosition
2023 Techniques and Efficiencies from Building a Real-Time DBMS
abstract
This paper describes a variety of techniques from over a decade of developing Aerospike (formerly Citrusleaf), a real-time DBMS that is being used in some of the world's largest mission-critical systems that require the highest levels of performance and availability. Such mission-critical systems have many requirements including the ability to make decisions within a strict real-time SLA (milliseconds) with no downtime, predictable performance so that the first and billionth customer gets the same experience, ability to scale up 10X (or even 100X) with no downtime, support strong consistency for applications that need it, synchronous and asynchronous replication with global transactional capabilities, and the ability to deploy in any public and private cloud environments. We describe how using efficient algorithms to optimize every area of the DBMS helps the system achieve these stringent requirements. Specifically, we describe, effective ways to shard, place and locate data across a set of nodes, efficient identification of cluster membership and cluster changes, efficiencies generated by using a 'smart' client, how to effectively use replications with two copies replication instead of three-copy, how to reduce the cost of the realtime data footprint by combining the use of memory with flash storage, self-managing clusters for ease of operation including elastic scaling, networking and CPU optimizations including NUMA pinning with multi-threading. The techniques and efficiencies described here have enabled hundreds of deployments to grow by many orders of magnitude with near complete uptime.
Andrew Gooding, Sunil Sayyaparaju, Thomas Lopatic, Kevin Porter, Ashish Shinde, B. Narendran
Proc. VLDB Endow.5