DBMS > IBM Cloudant vs. JanusGraph vs. Spark SQL

System Properties Comparison IBM Cloudant vs. JanusGraph vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

A Graph DBMS optimized for distributed clusters

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

Graph DBMS

Relational DBMS

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

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

www.ibm.com/products/cloudant

janusgraph.org

spark.apache.org/sql

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.janusgraph.org

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Linux Foundation; originally developed as Titan by Aurelius

Apache Software Foundation

Initial release

2010

2017

2014

Current release

0.6.3, February 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 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

Erlang

Java

Scala

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

Clojure
Java
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users can be defined per database

User authentification and security via Rexster Graph Server

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