DBMS > Amazon DynamoDB vs. BigchainDB vs. Newts vs. Postgres-XL vs. PouchDB

System Properties Comparison Amazon DynamoDB vs. BigchainDB vs. Newts vs. Postgres-XL vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

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

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

Time Series DBMS based on Cassandra

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

aws.amazon.com/dynamodb

www.bigchaindb.com

opennms.github.io/newts

www.postgres-xl.org

pouchdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

bigchaindb.readthedocs.io/en/latest

github.com/OpenNMS/newts/wiki

www.postgres-xl.org/documentation

pouchdb.com/guides

Developer

Amazon

OpenNMS Group

Apache Software Foundation

Initial release

2012

2016

2014

since 2012, originally named StormDB

2012

Current release

10 R1, October 2018

7.1.1, June 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

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

Java

JavaScript

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
macOS

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

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

via views

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

HTTP REST
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Haskell
Java
JavaScript
Python
Ruby

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

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

ACID

MVCC

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

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)

yes

fine grained access rights according to SQL-standard

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