DBMS > gStore vs. IBM Cloudant vs. LokiJS vs. Spark SQL

System Properties Comparison gStore vs. IBM Cloudant vs. LokiJS vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

Database as a Service offering based on Apache CouchDB

In-memory JavaScript DBMS

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

Primary database model

Graph DBMS
RDF store

Document store

Relational DBMS

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

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

en.gstore.cn

www.ibm.com/products/cloudant

github.com/techfort/LokiJS

spark.apache.org/sql

Technical documentation

en.gstore.cn/#/enDocs

cloud.ibm.com/docs/Cloudant

techfort.github.io/LokiJS

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

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Apache Software Foundation

Initial release

2016

2010

2014

Current release

1.2, November 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD

commercial

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

C++

Erlang

JavaScript

Scala

Server operating systems

Linux

hosted

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

Linux
OS X
Windows

Data scheme

schema-free and OWL/RDFS-schema support

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

via views

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API
SPARQL 1.1

RESTful HTTP/JSON API

JavaScript API

JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

JavaScript

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a document possible

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Access rights for users can be defined per database

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More resources

DB-Engines blog posts

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1 December 2014, Matthias Gelbmann

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