DBMS > OrigoDB vs. SWC-DB vs. Valentina Server

System Properties Comparison OrigoDB vs. SWC-DB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A fully ACID in-memory object graph database

A high performance, scalable Wide Column DBMS

Object-relational database and reports server

Primary database model

Document store
Object oriented DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

origodb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.valentina-db.net

Technical documentation

origodb.com/docs

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

Developer

Robert Friberg et al

Alex Kashirin

Paradigma Software

Initial release

2009

under the name LiveDB

2020

1999

Current release

0.5, April 2021

5.7.5

License

Commercial or Open Source

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

.NET Client API
HTTP API
LINQ

Proprietary protocol
Thrift

ODBC

Supported programming languages

.Net

C++

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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 authorization

fine grained access rights according to SQL-standard

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