DBMS > JanusGraph vs. MarkLogic vs. PouchDB vs. RocksDB

System Properties Comparison JanusGraph vs. MarkLogic vs. PouchDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

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

Operational and transactional Enterprise NoSQL database

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Graph DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store

Key-value store

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

janusgraph.org

www.progress.com/marklogic

pouchdb.com

rocksdb.org

Technical documentation

docs.janusgraph.org

www.progress.com/marklogic/documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Linux Foundation; originally developed as Titan by Aurelius

MarkLogic Corp.

Apache Software Foundation

Facebook, Inc.

Initial release

2017

2001

2012

2013

Current release

0.6.3, February 2023

11.0, December 2022

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

JavaScript

C++

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X
Windows

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

Linux

Data scheme

yes

schema-free

Schema can be enforced

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

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL92

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

Clojure
Java
Python

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

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

can act as a resource manager in an XA/JTA transaction

yes

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

yes

In-memory capabilities

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

yes, with Range Indexes

yes

User concepts

Access control

User authentification and security via Rexster Graph Server

Role-based access control at the document and subdocument levels

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