DBMS > Hive vs. JaguarDB vs. mSQL vs. TDSQL for MySQL

System Properties Comparison Hive vs. JaguarDB vs. mSQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Performant, highly scalable DBMS for AI and IoT applications

mSQL (Mini SQL) is a simple and lightweight RDBMS

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.

Primary database model

Relational DBMS

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	59.76
Rank	#18	Overall
	#12	Relational DBMS

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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

hive.apache.org

www.jaguardb.com

hughestech.com.au/products/msql

www.tencentcloud.com/products/dcdb

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

www.jaguardb.com/support.html

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation

initially developed by Facebook

DataJaguar, Inc.

Hughes Technologies

Tencent

Initial release

2012

2015

1994

2013

Current release

3.1.3, April 2022

3.3 July 2023

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL V3.0

commercial

free licenses can be provided

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

Java

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

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

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

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

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

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.

User concepts

Access control

Access rights for users, groups and roles

rights management via user accounts

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

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13 May 2013, Paul Andlinger

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