DBMS > Oracle NoSQL vs. Trafodion vs. Valentina Server vs. Vitess

System Properties Comparison Oracle NoSQL vs. Trafodion vs. Valentina Server vs. Vitess

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Transactional SQL-on-Hadoop DBMS

Object-relational database and reports server

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.oracle.com/database/nosql/technologies/nosql

trafodion.apache.org

www.valentina-db.net

vitess.io

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

trafodion.apache.org/documentation.html

valentina-db.com/docs/dokuwiki/v5/doku.php

vitess.io/docs

Developer

Oracle

Apache Software Foundation, originally developed by HP

Paradigma Software

The Linux Foundation, PlanetScale

Initial release

2011

2014

1999

2013

Current release

23.3, December 2023

2.3.0, February 2019

5.7.5

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 2.0

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++, Java

Server operating systems

Linux
Solaris SPARC/x86

Linux

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

optional

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

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

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes, via HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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