DBMS > Amazon DynamoDB vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. RethinkDB vs. STSdb

System Properties Comparison Amazon DynamoDB vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. RethinkDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Cloud-based data warehousing service

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS

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

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

aws.amazon.com/dynamodb

firebase.google.com/products/firestore

www.ibm.com/products/db2/warehouse

rethinkdb.com

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/firestore

rethinkdb.com/docs

Developer

Amazon

Google

IBM

The Linux Foundation

since July 2017

STS Soft SC

Initial release

2012

2017

2014

2009

2011

Current release

2.4.1, August 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2

Open Source

GPLv2, commercial license available

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
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

primitive types and user defined types (classes)

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

.NET Client API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C#
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

PL/SQL, SQL PL

Triggers

yes

by integration with AWS Lambda

yes, with Cloud Functions

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

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

ACID

Atomic single-document 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 Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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