DBMS > Hive vs. HyperSQL vs. RDF4J vs. SQream DB

System Properties Comparison Hive vs. HyperSQL vs. RDF4J vs. SQream DB

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

RDF store

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

rdf4j.org/documentation

docs.sqream.com

Developer

Apache Software Foundation

initially developed by Facebook

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

SQream Technologies

Initial release

2012

2001

2004

2017

Current release

3.1.3, April 2022

2.7.2, June 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

based on BSD license

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.Net
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

All languages supporting JDBC/ODBC
Java

Java
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, SQL

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical 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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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