DBMS > Amazon DynamoDB vs. CouchDB vs. GridDB vs. STSdb

System Properties Comparison Amazon DynamoDB vs. CouchDB vs. GridDB vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Scalable in-memory time series database optimized for IoT and Big Data

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

Document store

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Key-value 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	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

aws.amazon.com/dynamodb

couchdb.apache.org

griddb.net

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchdb.org/en/stable

docs.griddb.net

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Toshiba Corporation

STS Soft SC

Initial release

2012

2005

2013

2011

Current release

3.3.3, December 2023

5.1, August 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

Erlang

C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

.NET Client API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate consistency within container, eventual consistency across containers

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

atomic operations within a single document possible

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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 can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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