DBMS > Apache Impala vs. Cubrid vs. Hyprcubd vs. RDF4J

System Properties Comparison Apache Impala vs. Cubrid vs. Hyprcubd vs. RDF4J

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Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Serverless Time Series DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Time Series DBMS

RDF store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

impala.apache.org

cubrid.com (korean)
cubrid.org (english)

hyprcubd.com (offline)

rdf4j.org

Technical documentation

impala.apache.org/impala-docs.html

cubrid.org/manuals

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CUBRID Corporation, CUBRID Foundation

Hyprcubd, Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2013

2008

2004

Current release

4.1.0, June 2022

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

C, C++, Java

Java

Server operating systems

Linux

Linux
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

gRPC (https)

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

token access

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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