DBMS > JaguarDB vs. Sadas Engine vs. TDSQL for MySQL vs. Valentina Server

System Properties Comparison JaguarDB vs. Sadas Engine vs. TDSQL for MySQL vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Object-relational database and reports server

Primary database model

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.jaguardb.com

www.sadasengine.com

www.tencentcloud.com/products/dcdb

www.valentina-db.net

Technical documentation

www.jaguardb.com/support.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.tencentcloud.com/document/product/1042

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

Developer

DataJaguar, Inc.

SADAS s.r.l.

Tencent

Paradigma Software

Initial release

2015

2006

2013

1999

Current release

3.3 July 2023

8.0

5.7.5

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

AIX
Linux
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

ODBC

Supported programming languages

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
PHP
Python
Ruby

.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

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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