DBMS > Hive vs. IRONdb vs. RDF4J vs. RocksDB vs. TypeDB

System Properties Comparison Hive vs. IRONdb vs. RDF4J vs. RocksDB vs. TypeDB

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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

hive.apache.org

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

rdf4j.org

rocksdb.org

typedb.com

Technical documentation

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

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

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

typedb.com/docs

Developer

Apache Software Foundation

initially developed by Facebook

Circonus LLC.

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

Facebook, Inc.

Vaticle

Initial release

2012

2017

2004

2013

2016

Current release

3.1.3, April 2022

V0.10.20, January 2018

8.11.4, April 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Open Source

GPL Version 3, commercial licenses available

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

C++

Java

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

Linux

Linux
OS X
Windows

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

SQL

Support of SQL

SQL-like DML and DDL statements

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

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

C++ API
Java API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

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

C
C++
Go
Java
Perl
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

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

Sharding

Automatic, metric affinity per node

none

horizontal partitioning

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

none

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Isolation support depends on the API used

yes

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

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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