DBMS > H2 vs. Stardog vs. Tibero vs. Vitess

System Properties Comparison H2 vs. Stardog vs. Tibero vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

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

A secure RDBMS, designed for easy portability from Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.h2database.com

www.stardog.com

us.tmaxsoft.com/products/tibero

vitess.io

Technical documentation

www.h2database.com/html/main.html

docs.stardog.com

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

vitess.io/docs

Developer

Thomas Mueller

Stardog-Union

TmaxSoft

The Linux Foundation, PlanetScale

Initial release

2005

2010

2003

2013

Current release

2.2.220, July 2023

7.3.0, May 2020

6, April 2015

15.0.2, December 2022

License

Commercial or Open Source

Open Source

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

commercial

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

commercial

Open Source

Apache Version 2.0, commercial licenses available

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 and Assembler

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux
macOS

Data scheme

yes

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.

Import/export of XML data possible

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions and aggregates, HTTP Server extensions in Java

Persistent Stored Procedure (PSM)

yes

proprietary syntax

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by range, hash, list or composite

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

planned for next version

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

Users with fine-grained authorization concept

no user groups or roles

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