DBMS > Amazon DocumentDB vs. Amazon DynamoDB vs. GridDB vs. RRDtool

System Properties Comparison Amazon DocumentDB vs. Amazon DynamoDB vs. GridDB vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store

Document store
Key-value store

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/documentdb

aws.amazon.com/dynamodb

griddb.net

oss.oetiker.ch/rrdtool

Technical documentation

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/dynamodb

docs.griddb.net

oss.oetiker.ch/rrdtool/doc

Developer

Amazon

Toshiba Corporation

Tobias Oetiker

Initial release

2019

2012

2013

1999

Current release

5.1, August 2022

1.8.0, 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

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

Open Source

GPL V2 and FLOSS

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

in-process shared library
Pipes

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency within container, eventual consistency across containers

none

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

ACID

ACID across one or more tables within a single AWS account and region

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

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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