DBMS > GigaSpaces vs. Lovefield vs. Microsoft Azure Table Storage vs. MySQL vs. OrigoDB

System Properties Comparison GigaSpaces vs. Lovefield vs. Microsoft Azure Table Storage vs. MySQL vs. OrigoDB

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

Embeddable relational database for web apps written in pure JavaScript

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial 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	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

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

Website

www.gigaspaces.com

google.github.io/lovefield

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

origodb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

origodb.com/docs

Developer

Gigaspaces Technologies

Google

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

Initial release

2000

2014

2012

1995

2009

under the name LiveDB

Current release

15.5, September 2020

2.1.12, February 2017

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, C++, .Net

JavaScript

C and C++

Server operating systems

Linux
macOS
Solaris
Windows

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

tested with Chrome, Firefox, IE, Safari

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

yes

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C++
Java
Python
Scala

JavaScript

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes, event driven architecture

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica 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

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

Transaction concepts

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

ACID

optimistic locking

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Role-based access control

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

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