DBMS > GigaSpaces vs. IBM Db2 warehouse vs. OpenEdge vs. RocksDB

System Properties Comparison GigaSpaces vs. IBM Db2 warehouse vs. OpenEdge vs. RocksDB

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Name

Description

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

Cloud-based data warehousing service

Application development environment with integrated database management system

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

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Trend Chart

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.gigaspaces.com

www.ibm.com/products/db2/warehouse

www.progress.com/openedge

rocksdb.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

documentation.progress.com/output/ua/OpenEdge_latest

github.com/facebook/rocksdb/wiki

Developer

Gigaspaces Technologies

IBM

Progress Software Corporation

Facebook, Inc.

Initial release

2000

2014

1984

2013

Current release

15.5, September 2020

OpenEdge 12.2, March 2020

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

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

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

close to SQL 92

APIs and other access methods

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

.NET Client API
JDBC
ODBC
OLE DB

JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C++
Java
Python
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Progress proprietary ABL (Advanced Business Language)

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Source-replica replication

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

yes

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

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Users and groups

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