DBMS > Amazon DynamoDB vs. CouchDB vs. Derby vs. IRONdb vs. Kinetica

System Properties Comparison Amazon DynamoDB vs. CouchDB vs. Derby vs. IRONdb vs. Kinetica

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Fully vectorized database across both GPUs and CPUs

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS
Time Series 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	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

aws.amazon.com/dynamodb

couchdb.apache.org

db.apache.org/derby

www.circonus.com/solutions/time-series-database/

www.kinetica.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchdb.org/en/stable

db.apache.org/derby/manuals/index.html

docs.circonus.com/irondb/category/getting-started

docs.kinetica.com

Developer

Amazon

Apache Software Foundation

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

Apache Software Foundation

Circonus LLC.

Kinetica

Initial release

2012

2005

1997

2017

2012

Current release

3.3.3, December 2023

10.17.1.0, November 2023

V0.10.20, January 2018

7.1, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java

C and C++

C, C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC

HTTP API

JDBC
ODBC
RESTful HTTP 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

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

Java Stored Procedures

yes, in Lua

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

configurable replication factor, datacenter aware

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency or Eventual Consistency depending on configuration

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

atomic operations within a single document possible

ACID

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

GPU vRAM or System RAM

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

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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