DBMS > Altibase vs. HEAVY.AI vs. Lovefield vs. RDF4J

System Properties Comparison Altibase vs. HEAVY.AI vs. Lovefield vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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.

Primary database model

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

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

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

altibase.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

rdf4j.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.heavy.ai

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

rdf4j.org/documentation

Developer

Altibase

HEAVY.AI, Inc.

Google

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

Initial release

1999

2016

2014

2004

Current release

v7.3, 2023, August 2023

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

C++ and CUDA

JavaScript

Java

Server operating systems

AIX
HP-UX
Linux

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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

ANSI SQL-92

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
Thrift
Vega

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

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

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

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