DBMS > Apache Hive vs. JSqlDb vs. Transwarp KunDB

System Properties Comparison Apache Hive vs. JSqlDb vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

JavaScript Query Language Database, stores JavaScript objects and primitives

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	53.09
Rank	#18	Overall
	#12	Relational DBMS

Score	0.02
Rank	#375	Overall
	#156	Relational DBMS

Website

hive.apache.org

jsqldb.org (offline)

www.transwarp.cn/en/product/kundb

Technical documentation

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

Developer

Apache Software Foundation

initially developed by Facebook

Konrad von Backstrom

Transwarp

Initial release

2012

2018

Current release

3.1.3, April 2022

0.8, December 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

schema-free

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

yes

APIs and other access methods

JDBC
ODBC
Thrift

Supported programming languages

C++
Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

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

using RocksDB

yes

User concepts

Access control

Access rights for users, groups and roles

yes

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