DBMS > Amazon CloudSearch vs. Amazon DynamoDB vs. Infobright vs. Riak TS

System Properties Comparison Amazon CloudSearch vs. Amazon DynamoDB vs. Infobright vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Search engine

Document store
Key-value store

Relational DBMS

Time Series DBMS

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

Score	1.86
Rank	#133	Overall
	#12	Search engines

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/dynamodb

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/dynamodb

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

Developer

Amazon

Ignite Technologies Inc.; formerly InfoBright Inc.

Open Source, formerly Basho Technologies

Initial release

2012

2005

2015

Current release

3.0.0, September 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

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

Server operating systems

hosted

Linux
Windows

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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 search fields are automatically indexed

yes

Knowledge Grid Technology used instead

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

Erlang

Triggers

yes

by integration with AWS Lambda

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets 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

ACID

Concurrency

Support for concurrent manipulation of data

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

authentication via encrypted signatures

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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