DBMS > Apache Kylin vs. Derby vs. Hive

System Properties Comparison Apache Kylin vs. Derby vs. Hive

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Relational DBMS

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

Score	1.75
Rank	#172	Overall
	#83	Relational DBMS

Score	6.86
Rank	#61	Overall
	#34	Relational DBMS

Score	73.61
Rank	#17	Overall
	#11	Relational DBMS

Website

kylin.apache.org

db.apache.org/derby

hive.apache.org

Technical documentation

kylin.apache.org/docs

db.apache.org/derby/manuals/index.html

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

Developer

Apache Software Foundation, originally contributed from eBay Inc

Apache Software Foundation

initially developed by Facebook

Initial release

2015

1997

2012

Current release

3.1.0, July 2020

10.16.1.1, May 2022

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache Version 2

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

Linux

All OS with a Java VM

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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

JDBC
ODBC
Thrift

Supported programming languages

Java

C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

Immediate Consistency

Eventual 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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Recent citations in the news

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