DBMS > Hive vs. LeanXcale vs. Oracle Coherence vs. Trafodion

System Properties Comparison Hive vs. LeanXcale vs. Oracle Coherence vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Oracles in-memory data grid solution

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

hive.apache.org

www.leanxcale.com

www.oracle.com/java/coherence

trafodion.apache.org

Technical documentation

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

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

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

initially developed by Facebook

LeanXcale

Oracle

Apache Software Foundation, originally developed by HP

Initial release

2012

2015

2007

2014

Current release

3.1.3, April 2022

14.1, August 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, Java

Server operating systems

All OS with a Java VM

Linux

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

through Apache Derby

yes

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JCache
JPA
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

C
Java
Scala

.Net
C++
Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate 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

ACID

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

fine grained access rights according to SQL-standard

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