Proceedings ArticleDOI
Dynamo: amazon's highly available key-value store
Giuseppe deCandia,Deniz Hastorun,Madan Mohan Rao Jampani,Gunavardhan Kakulapati,Avinash Lakshman,Alex Pilchin,Swaminathan Sivasubramanian,Peter Sven Vosshall,Werner Vogels +8 more
- Vol. 41, Iss: 6, pp 205-220
TLDR
D Dynamo is presented, a highly available key-value storage system that some of Amazon's core services use to provide an "always-on" experience and makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.Abstract:
Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems.This paper presents the design and implementation of Dynamo, a highly available key-value storage system that some of Amazon's core services use to provide an "always-on" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.read more
Citations
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Proceedings ArticleDOI
StoreGPU: exploiting graphics processing units to accelerate distributed storage systems
TL;DR: StoreGPU is designed, a library that accelerates a number of hashing based primitives popular in distributed storage system implementations that enable up to eight-fold performance gains on synthetic benchmarks as well as on a high-level application: the online similarity detection between large data files.
Proceedings ArticleDOI
Multi-dimensional Index on Hadoop Distributed File System
TL;DR: Experimental evaluation demonstrates that the built-in index structure can efficiently improve query performance, and serve as cornerstones for structured or semi-structured data management.
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What consistency does your key-value store actually provide?
TL;DR: By analyzing the trace of interactions between the client machines and a key-value store, the algorithms can report whether the trace is safe, regular, or atomic, and if not, how many violations there are in the trace.
Journal ArticleDOI
SlimDB: a space-efficient key-value storage engine for semi-sorted data
TL;DR: By applying design techniques, the new implementation of a key-value store, SlimDB, can be two to three times faster, use less memory to cache metadata indices, and show lower tail latency in read operations compared to popular LSM-tree implementations such as LevelDB and RocksDB.
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SLM-DB: Single-Level Key-Value Store with Persistent Memory
TL;DR: This paper presents a novel KV store, the Single-Level Merge DB (SLM-DB), which takes advantage of both the B+-tree index and the Log-Structured Merge Trees (LSM-tree) approach by making the best use of fast persistent memory.
References
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