DBMS > Hive vs. IRONdb vs. RDF4J vs. Riak KV vs. SAP HANA

System Properties Comparison Hive vs. IRONdb vs. RDF4J vs. Riak KV vs. SAP HANA

Editorial information provided by DB-Engines

Name

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

Description

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

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

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

hive.apache.org

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

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

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

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

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/hana

Developer

Apache Software Foundation

initially developed by Facebook

Circonus LLC.

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

OpenSource, formerly Basho Technologies

SAP

Initial release

2012

2017

2004

2009

2010

Current release

3.1.3, April 2022

V0.10.20, January 2018

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

Erlang

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

Linux
OS X

Appliance or cloud-service

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

yes

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

APIs and other access methods

JDBC
ODBC
Thrift

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

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

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in Lua

yes

Erlang

SQLScript, R

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

yes, using Riak Security

yes

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