DBMS > Amazon DynamoDB vs. CouchDB vs. Drizzle vs. LeanXcale vs. OrientDB

System Properties Comparison Amazon DynamoDB vs. CouchDB vs. Drizzle vs. LeanXcale vs. OrientDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

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

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

aws.amazon.com/dynamodb

couchdb.apache.org

www.leanxcale.com

orientdb.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchdb.org/en/stable

www.orientdb.com/docs/last/index.html

Developer

Amazon

Apache Software Foundation

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

Drizzle project, originally started by Brian Aker

LeanXcale

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2005

2008

2015

2010

Current release

3.3.3, December 2023

7.2.4, September 2012

3.2.29, March 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

GNU GPL

commercial

Open Source

Apache version 2

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

C++

Java

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

through Apache Derby

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON 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++
Java
PHP

C
Java
Scala

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

Java, Javascript

Triggers

yes

by integration with AWS Lambda

yes

hooks for callbacks inside the server can be used.

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles; record level security configurable

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