DBMS > Amazon DynamoDB vs. Ehcache vs. Firebase Realtime Database vs. Realm vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. Ehcache vs. Firebase Realtime Database vs. Realm vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

A widely adopted Java cache with tiered storage options

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Key-value store

Document store

Relational 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	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/dynamodb

www.ehcache.org

firebase.google.com/products/realtime-database

realm.io

Technical documentation

docs.aws.amazon.com/dynamodb

www.ehcache.org/documentation

firebase.google.com/docs/database

realm.io/docs

Developer

Amazon

Terracotta Inc, owned by Software AG

Google

acquired by Google 2014

Realm, acquired by MongoDB in May 2019

Teradata

Initial release

2012

2009

2012

2014

2005

Current release

3.10.0, March 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

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

Server operating systems

hosted

All OS with a Java VM

hosted

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JCache

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

Java
JavaScript
Objective-C

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

limited functionality with using 'rules'

runs within the applications so server-side scripts are unnecessary

R packages

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

Callbacks are triggered when data changes

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

User concepts

Access control

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

yes, based on authentication and database rules

yes

fine grained access rights according to SQL-standard

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