DBMS > AgensGraph vs. Hive vs. IRONdb vs. OpenEdge vs. RDF4J

System Properties Comparison AgensGraph vs. Hive vs. IRONdb vs. OpenEdge vs. RDF4J

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Application development environment with integrated database management system

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

Primary database model

Graph DBMS
Relational DBMS

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

bitnine.net/agensgraph

hive.apache.org

www.circonus.com/solutions/time-series-database/

www.progress.com/openedge

rdf4j.org

Technical documentation

bitnine.net/documentation

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

docs.circonus.com/irondb/category/getting-started

documentation.progress.com/output/ua/OpenEdge_latest

rdf4j.org/documentation

Developer

Bitnine Global Inc.

Apache Software Foundation

initially developed by Facebook

Circonus LLC.

Progress Software Corporation

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

Initial release

2016

2012

2017

1984

2004

Current release

2.1, December 2018

3.1.3, April 2022

V0.10.20, January 2018

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2

commercial

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

Java

C and C++

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

depending on used data model

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

close to SQL 92

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
Thrift

HTTP API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
Java
JavaScript
Python

C++
Java
PHP
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Progress proprietary ABL (Advanced Business Language)

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Automatic, metric affinity per node

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

configurable replication factor, datacenter aware

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

Immediate Consistency

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Users and groups

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