DBMS > Amazon CloudSearch vs. Amazon DynamoDB vs. BigObject vs. Ehcache vs. Microsoft Azure SQL Database

System Properties Comparison Amazon CloudSearch vs. Amazon DynamoDB vs. BigObject vs. Ehcache vs. Microsoft Azure SQL Database

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

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Search engine

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial 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	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/dynamodb

bigobject.io

www.ehcache.org

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/dynamodb

docs.bigobject.io

www.ehcache.org/documentation

docs.microsoft.com/en-us/azure/azure-sql

Developer

Amazon

BigObject, Inc.

Terracotta Inc, owned by Software AG

Microsoft

Initial release

2012

2015

2009

2010

Current release

3.10.0, March 2022

V12

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

commercial

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

Java

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

schema-free

yes

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP API

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

JCache

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Transact SQL

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

Sharding

by using Terracotta Server

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

none

yes

by using Terracotta Server

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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