DBMS > Amazon SimpleDB vs. Apache Impala vs. RethinkDB vs. Riak KV vs. SwayDB

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. RethinkDB vs. Riak KV vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Analytic DBMS for Hadoop

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Distributed, fault tolerant key-value store

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Key-value store

Secondary database models

Document store

Spatial DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

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

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

aws.amazon.com/simpledb

impala.apache.org

rethinkdb.com

swaydb.simer.au

Technical documentation

docs.aws.amazon.com/simpledb

impala.apache.org/impala-docs.html

rethinkdb.com/docs

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

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

The Linux Foundation

since July 2017

OpenSource, formerly Basho Technologies

Simer Plaha

Initial release

2007

2013

2009

2018

Current release

4.1.0, June 2022

2.4.1, August 2020

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

GNU Affero GPL V3.0

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

C++

Erlang

Scala

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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 columns are indexed automatically

yes

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

Triggers

Client-side triggers through changefeeds

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

range based

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate 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

Concurrent data updates can be detected by the application

Atomic single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

users and table-level permissions

yes, using Riak Security

More information provided by the system vendor

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More resources

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