Amazon Dynamo

Feb 20, 20143 likes1,304 views

Dynamo is a highly available key-value storage system built by Amazon to power its e-commerce platform. It uses consistent hashing to partition data across nodes in a ring topology and achieves high availability of writes through techniques like vector clocks, hinted handoff, and quorums. Dynamo provides simple interfaces to store and retrieve data identified by unique keys at massive scales with low latency despite failures through an eventually consistent model.

Dynamo: Amazon’s Highly Available Key-Value Store
Farley Lai
University of Iowa
poyuan-lai@uiowa.edu

February 21, 2014

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

1 / 14

Motivation

MapReduce processes big data in a parallel and distributed fashion.
Daynamo forms the foundation of big data, namely, the storage.

Shopping Cart
Clients tend to insert and update items frequenty but review the cart to
check out only at the end. Is it fun for the sytem to always ask you to
retry later in minutes whenever there is an item inserted/updated in the
shopping cart?

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

2 / 14

SOA of Amazon’s Platform

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

3 / 14

Roles
Service Provider: Amazon
Service: Dynamo, the storage service
Customer: application/service vendors
Client: applications/services
User: human and/or bots

Service Level Agreements (SLA)
SLA are contracts signed by service providers and customers, specifying
the quality of service guaranteed for a client access distribution.
Example: service guaranteeing that it will provide a response within
300ms for 99.9% of its requests for a peak client load of 500 requests per
second.
Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

4 / 14

What is Dynamo?

A distributed key-value storage service built on a ring topology with
high availability for writes
eventual consistency

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

5 / 14

Requirements and Assumptions

Requirements
Simple read/write to data items identiﬁed by unique keys
ACID: automicity, consistency, isolation and durability
SLA: latency constraints on the 99.9th percentile of the
distribution
Assumptions
Trusted environment and machines without security concerns

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

6 / 14

Problems, Techniques and Advantages

Problems
Partitioning
High write availability
Temporary failures

Permanent failures
Membership

Farley Lai (UIOWA)

Techniques

Advantages

Consistent Hashing
Vector clocks with
conlict resolution
Sloppy
Quorum,
hinted handoﬀ

Incremental Scalability
Version size is decoupled
from update rates
High availability and durability guarantee despite
some unavailable replicas
Fast replica synchronization
decentralized registry for
storing membership and
liveness info

Merkle trees
Gossip protocol

Amazon Dynamo (Big Data)

February 21, 2014

7 / 14

Partitioning

Consistent hashing
1

key space

2

tokens assignment

3

replication

4

load distribution

5

node availability

6

node capacity

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

8 / 14

Data Versioning

Operations
1

read()⇒get()

2

write()⇒put()

3

conﬂict resolution

4

vector clock

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

9 / 14

Sloppy Quorum

1

R(2) + W (2) > N(3)

2

latency

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

10 / 14

Replica Synchronization

Figure : Merkle hash tree1

Farley Lai (UIOWA)

Figure : Merkle hash tree2

Amazon Dynamo (Big Data)

February 21, 2014

11 / 14

Evaluation: latency

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

12 / 14

Evaluation: load balance

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

13 / 14

Evaluation: write buﬀer

Farley Lai (UIOWA)

Amazon Dynamo (Big Data)

February 21, 2014

14 / 14

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Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025 https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/ Is AI just another technology, or does it fundamentally change the way we live and think? Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater. At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts. At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.

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