DBMS > GigaSpaces vs. Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. SAP HANA

System Properties Comparison GigaSpaces vs. Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. SAP HANA

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

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

Application development environment with integrated database management system

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.gigaspaces.com

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

www.progress.com/openedge

realm.io

www.sap.com/products/hana.html

Technical documentation

docs.gigaspaces.com/latest/landing.html

documentation.progress.com/output/ua/OpenEdge_latest

realm.io/docs

help.sap.com/hana

Developer

Gigaspaces Technologies

Microsoft

Progress Software Corporation

Realm, acquired by MongoDB in May 2019

SAP

Initial release

2000

2012

1984

2014

2010

Current release

15.5, September 2020

OpenEdge 12.2, March 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

Server operating systems

Linux
macOS
Solaris
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

close to SQL 92

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

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

Progress proprietary ABL (Advanced Business Language)

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

SQLScript, R

Triggers

yes, event driven architecture

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

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

Source-replica replication

none

yes

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

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

Role-based access control

Access rights based on private key authentication or shared access signatures

Users and groups

yes

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