DBMS > Apache Hive vs. Oracle Coherence vs. Transwarp KunDB

System Properties Comparison Apache Hive vs. Oracle Coherence vs. Transwarp KunDB

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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

Oracles in-memory data grid solution

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	53.09
Rank	#18	Overall
	#12	Relational DBMS

Score	1.74
Rank	#131	Overall
	#22	Key-value stores

Score	0.02
Rank	#375	Overall
	#156	Relational DBMS

Website

hive.apache.org

www.oracle.com/java/coherence

www.transwarp.cn/en/product/kundb

Technical documentation

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

Transwarp

Initial release

2012

2007

Current release

3.1.3, April 2022

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

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

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

JCache
JPA
RESTful HTTP API

Supported programming languages

C++
Java
PHP
Python

.Net
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Access rights for users, groups and roles

authentification to access the cache via certificates or http basic authentication

yes

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