DBMS > Amazon DynamoDB vs. Apache Drill vs. Microsoft Azure Cosmos DB vs. Riak KV vs. Sequoiadb

System Properties Comparison Amazon DynamoDB vs. Apache Drill vs. Microsoft Azure Cosmos DB vs. Riak KV vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Globally distributed, horizontally scalable, multi-model database service

Distributed, fault tolerant key-value store

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store
Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/dynamodb

drill.apache.org

azure.microsoft.com/services/cosmos-db

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

drill.apache.org/docs

learn.microsoft.com/azure/cosmos-db

www.tiot.jp/riak-docs/riak/kv/latest

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon

Apache Software Foundation

Microsoft

OpenSource, formerly Basho Technologies

Sequoiadb Ltd.

Initial release

2012

2014

2009

2013

Current release

1.20.3, January 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
OS X

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

oid, date, timestamp, binary, regex

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All properties auto-indexed by default

restricted

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API
Native Erlang Interface

proprietary protocol using JSON

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

Erlang

JavaScript

Triggers

yes

by integration with AWS Lambda

JavaScript

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

Multi-item ACID transactions with snapshot isolation within a partition

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Depending on the underlying data source

Access rights can be defined down to the item level

yes, using Riak Security

simple password-based access control

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