DBMS > HyperSQL vs. Lovefield vs. RDF4J vs. StarRocks

System Properties Comparison HyperSQL vs. Lovefield vs. RDF4J vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Relational DBMS

RDF store

Relational DBMS

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

hsqldb.org

google.github.io/lovefield

rdf4j.org

www.starrocks.io

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

github.com/google/lovefield/blob/master/docs/spec_index.md

rdf4j.org/documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Google

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

The Linux Foundation

since Feb 2023

Initial release

2001

2014

2004

2020

Current release

2.7.2, June 2023

2.1.12, February 2017

2.5.3, March 2023

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 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

JavaScript

Java

C++, Java

Server operating systems

All OS with a Java VM

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

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

RDF Schemas

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

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

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

JDBC
MySQL protocol

Supported programming languages

All languages supporting JDBC/ODBC
Java

JavaScript

Java
PHP
Python

Java

Server-side scripts

Stored procedures

Java, SQL

yes

user defined functions

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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