DBMS > GridDB vs. Oracle vs. OrientDB vs. Tibero

System Properties Comparison GridDB vs. Oracle vs. OrientDB vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Widely used RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

griddb.net

www.oracle.com/database

orientdb.org

us.tmaxsoft.com/products/tibero

Technical documentation

docs.griddb.net

docs.oracle.com/en/database

www.orientdb.com/docs/last/index.html

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

Developer

Toshiba Corporation

Oracle

OrientDB LTD; CallidusCloud; SAP

TmaxSoft

Initial release

2013

1980

2010

2003

Current release

5.1, August 2022

23c, September 2023

3.2.29, March 2024

6, April 2015

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

restricted free version is available

Open Source

Apache version 2

commercial

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

C++

C and C++

Java

C and Assembler

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java JDK (>= JDK 6)

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

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

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

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Java, Javascript

Persistent Stored Procedure (PSM)

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

can be realized in PL/SQL

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID at container level

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

planned for next version

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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