DBMS > Quasardb vs. Valentina Server

System Properties Comparison Quasardb vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Distributed, high-performance timeseries database

Object-relational database and reports server

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.19
Rank	#285	Overall
	#22	Time Series DBMS

Score	0.21
Rank	#282	Overall
	#131	Relational DBMS

Website

quasardb.net

www.valentina-db.net

Technical documentation

doc.quasardb.net

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

Developer

quasardb

Paradigma Software

Initial release

2009

1999

Current release

3.1, January 2019

5.7.5

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

ODBC

Supported programming languages

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more

Competitive advantages

High performance in a cost-effective small package Real-time results for even large...
» more

Typical application scenarios

Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more

Key customers

Large EU investment banks US based hedge funds Orolia Tellmeplus
» more

Market metrics

Has been running in very demanding production environments since 2013 Rapid adoption...
» more

Licensing and pricing models

Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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