DBMS > Amazon DynamoDB vs. Axibase vs. CouchDB vs. Elasticsearch vs. FatDB

System Properties Comparison Amazon DynamoDB vs. Axibase vs. CouchDB vs. Elasticsearch vs. FatDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Primary database model

Document store
Key-value store

Time Series DBMS

Document store

Search engine

Document store
Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS
Vector 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	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Website

aws.amazon.com/dynamodb

axibase.com/docs/atsd/finance

couchdb.apache.org

www.elastic.co/elasticsearch

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchdb.org/en/stable

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Amazon

Axibase Corporation

Apache Software Foundation

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

Elastic

FatCloud

Initial release

2012

2013

2005

2010

2012

Current release

15585

3.3.3, December 2023

8.6, January 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache version 2

Open Source

Elastic License

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

Java

Erlang

Java

Server operating systems

hosted

Linux

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Windows

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

APIs and other access methods

RESTful HTTP API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
PHP
Python
R
Ruby

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

via applications

Triggers

yes

by integration with AWS Lambda

yes

by using the 'percolation' feature

yes

via applications

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

Source-replica replication

Multi-source replication
Source-replica replication

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

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

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.

Memcached and Redis integration

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

Can implement custom security layer via applications

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