DBMS > Amazon SimpleDB vs. BigchainDB vs. Google BigQuery vs. PouchDB vs. Tkrzw

System Properties Comparison Amazon SimpleDB vs. BigchainDB vs. Google BigQuery vs. PouchDB vs. Tkrzw

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

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

Large scale data warehouse service with append-only tables

JavaScript DBMS with an API inspired by CouchDB

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

aws.amazon.com/simpledb

www.bigchaindb.com

cloud.google.com/bigquery

pouchdb.com

dbmx.net/tkrzw

Technical documentation

docs.aws.amazon.com/simpledb

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigquery/docs

pouchdb.com/guides

Developer

Amazon

Google

Apache Software Foundation

Mikio Hirabayashi

Initial release

2007

2016

2010

2012

2020

Current release

7.1.1, June 2019

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Open Source

Apache Version 2.0

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

Python

JavaScript

C++

Server operating systems

hosted

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS

Data scheme

schema-free

yes

schema-free

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

All columns are indexed automatically

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

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

yes

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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