DBMS > Altibase vs. EsgynDB vs. HarperDB vs. RDF4J

System Properties Comparison Altibase vs. EsgynDB vs. HarperDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Primary database model

Relational DBMS

Document store

RDF store

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

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.55
Rank	#252	Overall
	#38	Document stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

Technical documentation

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

docs.harperdb.io/docs

rdf4j.org/documentation

Developer

Altibase

Esgyn

HarperDB

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

Initial release

1999

2015

2017

2004

Current release

v7.3, 2023, August 2023

3.1, August 2021

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free community edition available

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++, Java

Node.js

Java

Server operating systems

AIX
HP-UX
Linux

Linux

Linux
OS X

Linux
OS X
Unix
Windows

Data scheme

yes

dynamic schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

JSON data types

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 data manipulation statements

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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/ADO.Net

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

Java Stored Procedures

Custom Functions

since release 3.1

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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