DBMS > GridGain vs. IBM Db2 vs. LokiJS vs. SQLite vs. Transbase

System Properties Comparison GridGain vs. IBM Db2 vs. LokiJS vs. SQLite vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

In-memory JavaScript DBMS

Widely used embeddable, in-process RDBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.gridgain.com

www.ibm.com/products/db2

github.com/techfort/LokiJS

www.sqlite.org

www.transaction.de/en/products/transbase.html

Technical documentation

www.gridgain.com/docs/index.html

www.ibm.com/docs/en/db2

techfort.github.io/LokiJS

www.sqlite.org/docs.html

www.transaction.de/en/products/transbase/features.html

Developer

GridGain Systems, Inc.

IBM

Dwayne Richard Hipp

Transaction Software GmbH

Initial release

2007

1983

host version

2014

2000

1987

Current release

GridGain 8.5.1

12.1, October 2016

3.45.3 (15 April 2024), April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free version is available

Open Source

Public Domain

commercial

free development license

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

C and C++

JavaScript

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

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

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

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

yes

SQL-92 is not fully supported

yes

APIs and other access methods

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

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

yes

View functions in JavaScript

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

with separate tools (MQ, InfoSphere)

none

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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