DBMS > Couchbase vs. JanusGraph vs. Microsoft Azure Table Storage vs. Netezza vs. PouchDB

System Properties Comparison Couchbase vs. JanusGraph vs. Microsoft Azure Table Storage vs. Netezza vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A Wide Column Store for rapid development using massive semi-structured datasets

Data warehouse and analytics appliance part of IBM PureSystems

JavaScript DBMS with an API inspired by CouchDB

Primary database model

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	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.couchbase.com

janusgraph.org

azure.microsoft.com/en-us/services/storage/tables

www.ibm.com/products/netezza

pouchdb.com

Technical documentation

docs.couchbase.com

docs.janusgraph.org

pouchdb.com/guides

Developer

Couchbase, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

IBM

Apache Software Foundation

Initial release

2011

2017

2012

2000

2012

Current release

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

0.6.3, February 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

commercial

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

C, C++, Go and Erlang

Java

JavaScript

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix
Windows

hosted

Linux

included in appliance

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

Data scheme

schema-free

yes

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

via views

SQL

Support of SQL

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

yes

APIs and other access methods

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

JDBC
ODBC
OLE DB

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java
Python

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

Server-side scripts

Stored procedures

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

yes

View functions in JavaScript

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Ephemeral buckets

yes

User concepts

Access control

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

User authentification and security via Rexster Graph Server

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

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