DBMS > GigaSpaces vs. mSQL vs. OrigoDB vs. SQLite vs. SWC-DB

System Properties Comparison GigaSpaces vs. mSQL vs. OrigoDB vs. SQLite vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Wide column store

Secondary database models

Graph DBMS
Search engine

Time Series DBMS

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.gigaspaces.com

hughestech.com.au/products/msql

origodb.com

www.sqlite.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

origodb.com/docs

www.sqlite.org/docs.html

Developer

Gigaspaces Technologies

Hughes Technologies

Robert Friberg et al

Dwayne Richard Hipp

Alex Kashirin

Initial release

2000

1994

2009

under the name LiveDB

2000

2020

Current release

15.5, September 2020

4.4, October 2021

3.45.3 (15 April 2024), April 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

free licenses can be provided

Open Source

Public Domain

Open Source

GPL V3

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++

Server operating systems

Linux
macOS
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

server-less

Linux

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

not rigid because of 'dynamic typing' concept.

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.

XML can be used for describing objects metadata

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Proprietary protocol
Thrift

Supported programming languages

.Net
C++
Java
Python
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

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++

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

none

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.