DBMS > GigaSpaces vs. mSQL vs. NSDb vs. OrigoDB vs. VoltDB

System Properties Comparison GigaSpaces vs. mSQL vs. NSDb vs. OrigoDB vs. VoltDB

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS
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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
	#41	Time Series DBMS

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

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.gigaspaces.com

hughestech.com.au/products/msql

nsdb.io

origodb.com

www.voltdb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

nsdb.io/Architecture

origodb.com/docs

docs.voltdb.com

Developer

Gigaspaces Technologies

Hughes Technologies

Robert Friberg et al

VoltDB Inc.

Initial release

2000

1994

2017

2009

under the name LiveDB

2010

Current release

15.5, September 2020

4.4, October 2021

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

free licenses can be provided

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, Scala

Java, C++

Server operating systems

Linux
macOS
Solaris
Windows

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

Linux
macOS

Linux
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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.

XML can be used for describing objects metadata

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

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

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

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

JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C++
Java
Python
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Scala

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes, event driven architecture

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

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

Multi-source replication
Source-replica replication

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

Eventual Consistency

Foreign keys

Referential integrity

depending on model

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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