DBMS > BigchainDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. PouchDB vs. Warp 10

System Properties Comparison BigchainDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. PouchDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

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

JavaScript DBMS with an API inspired by CouchDB

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Graph DBMS
Key-value store

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.bigchaindb.com

azure.microsoft.com/services/cosmos-db

orientdb.org

pouchdb.com

www.warp10.io

Technical documentation

bigchaindb.readthedocs.io/en/latest

learn.microsoft.com/azure/cosmos-db

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

pouchdb.com/guides

www.warp10.io/content/02_Getting_started

Developer

Microsoft

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

SenX

Initial release

2016

2014

2010

2012

2015

Current release

3.2.29, March 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache version 2

Open Source

Apache License 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

Java

JavaScript

Java

Server operating systems

Linux

hosted

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

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

Linux
OS X
Windows

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

JSON 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 properties auto-indexed by default

yes

via views

SQL

Support of SQL

SQL-like query language

SQL-like query language, no joins

APIs and other access methods

CLI Client
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

JavaScript

Server-side scripts

Stored procedures

JavaScript

Java, Javascript

View functions in JavaScript

yes

WarpScript

Triggers

JavaScript

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

User concepts

Access control

yes

Access rights can be defined down to the item level

Access rights for users and roles; record level security configurable

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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