DBMS > eXtremeDB vs. Heroic vs. IRONdb vs. RDF4J vs. TypeDB

System Properties Comparison eXtremeDB vs. Heroic vs. IRONdb vs. RDF4J vs. TypeDB

Editorial information provided by DB-Engines

Name

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

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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.

TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

RDF store

Graph DBMS

The type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS

The data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS

The type-theoretic data model of TypeDB subsumes the relational database model.

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

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.65
Rank	#230	Overall
	#20	Graph DBMS
	#9	Object oriented DBMS
	#107	Relational DBMS

Website

www.mcobject.com

github.com/spotify/heroic

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

rdf4j.org

typedb.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

spotify.github.io/heroic

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

rdf4j.org/documentation

typedb.com/docs

Developer

McObject

Spotify

Circonus LLC.

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

Vaticle

Initial release

2001

2014

2017

2004

2016

Current release

8.2, 2021

V0.10.20, January 2018

2.28.3, June 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C and C++

Java

C and C++

Java

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

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.

support of XML interfaces available

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

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

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

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

Java
PHP
Python

All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

yes, in Lua

yes

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

configurable replication factor, datacenter aware

none

Synchronous replication via raft

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more

Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more

Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

McObject
17 November 2021, Electronic Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

Interview: Jeff Chang And Steve Graves Cover In-Memory Databases
17 December 2013, Electronic Design

Schneider Electric to collaborate with McObject
14 October 2015, Construction Week Online

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

provided by Google News

Modelling Biomedical Data for a Drug Discovery Knowledge Graph
6 October 2020, Towards Data Science

Speedb Goes Open Source With Its Speedb Data Engine, A Drop-in Replacement for RocksDB
9 November 2022, Business Wire

Building a Biomedical Knowledge Graph
28 June 2021, Towards Data Science

provided by Google News

Share this page