DBMS > GigaSpaces vs. H2 vs. RavenDB vs. Stardog vs. Transbase

System Properties Comparison GigaSpaces vs. H2 vs. RavenDB vs. Stardog vs. Transbase

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open Source Operational and Transactional Enterprise NoSQL Document Database

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	3.01
Rank	#101	Overall
	#17	Document stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

www.transaction.de/en/products/transbase.html

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.h2database.com/html/main.html

ravendb.net/docs

docs.stardog.com

www.transaction.de/en/products/transbase/features.html

Developer

Gigaspaces Technologies

Thomas Mueller

Hibernating Rhinos

Stardog-Union

Transaction Software GmbH

Initial release

2000

2005

2010

1987

Current release

15.5, September 2020

2.2.220, July 2023

5.4, July 2022

7.3.0, May 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

AGPL version 3, commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

free development license

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

C and C++

Server operating systems

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language (RQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

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

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C++
Java
Python
Scala

Java

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes, event driven architecture

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

Multi-source replication in HA-Cluster

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Authorization levels configured per client per database

Access rights for users and roles

fine grained access rights according to SQL-standard

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