DBMS > Transwarp StellarDB vs. Valentina Server vs. YottaDB

System Properties Comparison Transwarp StellarDB vs. Valentina Server vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

A distributed graph DBMS built for enterprise-level graph applications

Object-relational database and reports server

A fast and solid embedded Key-value store

Primary database model

Graph DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

www.transwarp.cn/en/product/stellardb

www.valentina-db.net

yottadb.com

Technical documentation

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

yottadb.com/resources/documentation

Developer

Transwarp

Paradigma Software

YottaDB, LLC

Initial release

1999

2001

Current release

5.7.5

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

Linux
OS X
Windows

Docker
Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

by using the Octo plugin

APIs and other access methods

OpenCypher

ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

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

yes

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

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provided by Google News

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