DBMS > GridGain vs. Kyligence Enterprise vs. LokiJS vs. STSdb

System Properties Comparison GridGain vs. Kyligence Enterprise vs. LokiJS vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A distributed analytics engine for big data, built on top of Apache Kylin

In-memory JavaScript DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Document store

Key-value store

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

www.gridgain.com

kyligence.io/kyligence-enterprise

github.com/techfort/LokiJS

github.com/STSSoft/STSdb4

Technical documentation

www.gridgain.com/docs/index.html

techfort.github.io/LokiJS

Developer

GridGain Systems, Inc.

Kyligence, Inc.

STS Soft SC

Initial release

2007

2016

2014

2011

Current release

GridGain 8.5.1

4.0.8, September 2015

License

Commercial or Open Source

commercial, open source

commercial

Open Source

GPLv2, commercial license available

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++, .Net, Python, REST, SQL

Java

JavaScript

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux

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

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

ANSI-99 for query and DML statements, subset of DDL

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
RESTful HTTP API

JavaScript API

.NET Client API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

C#
Java

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

View functions in JavaScript

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

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

Role-based access control
Security Hooks for custom implementations

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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