DBMS > Amazon SimpleDB vs. BaseX vs. BigchainDB vs. Couchbase

System Properties Comparison Amazon SimpleDB vs. BaseX vs. BigchainDB vs. Couchbase

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Primary database model

Key-value store

Native XML DBMS

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Website

aws.amazon.com/simpledb

basex.org

www.bigchaindb.com

www.couchbase.com

Technical documentation

docs.aws.amazon.com/simpledb

docs.basex.org

bigchaindb.readthedocs.io/en/latest

docs.couchbase.com

Developer

Amazon

BaseX GmbH

Couchbase, Inc.

Initial release

2007

2016

2011

Current release

10.7, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

AGPL v3

Open Source

Business Source License (BSL 1.1); Commercial licenses also 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

Java

Python

C, C++, Go and Erlang

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

XQuery supports types

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

All columns are indexed automatically

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

CLI Client
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Triggers

yes

via events

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

Automatic Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Multi-source replication

including cross data center replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

selectable on a per-operation basis

Foreign keys

Referential integrity

Transaction concepts

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

Concurrent data updates can be detected by the application

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept on 4 levels

yes

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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