DBMS > Amazon DynamoDB vs. Firebase Realtime Database vs. Percona Server for MongoDB vs. Realm vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. Firebase Realtime Database vs. Percona Server for MongoDB 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

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

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	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/dynamodb

firebase.google.com/products/realtime-database

www.percona.com/mongodb/software/percona-server-for-mongodb

realm.io

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/database

docs.percona.com/percona-distribution-for-mongodb

realm.io/docs

Developer

Amazon

Google

acquired by Google 2014

Percona

Realm, acquired by MongoDB in May 2019

Teradata

Initial release

2012

2015

2014

2005

Current release

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

GPL Version 2

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

C++

Server operating systems

hosted

Linux

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

Android
iOS
JavaScript API
RESTful HTTP API

proprietary protocol using JSON

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.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'

JavaScript

runs within the applications so server-side scripts are unnecessary

R packages

Triggers

yes

by integration with AWS Lambda

Callbacks are triggered when data changes

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

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

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

via In-Memory Engine

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

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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