DBMS > IRONdb vs. JanusGraph vs. Riak TS vs. Stardog

System Properties Comparison IRONdb vs. JanusGraph vs. Riak TS vs. Stardog

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Editorial information provided by DB-Engines

Name

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

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

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

janusgraph.org

www.stardog.com

Technical documentation

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

docs.janusgraph.org

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

docs.stardog.com

Developer

Circonus LLC.

Linux Foundation; originally developed as Titan by Aurelius

Open Source, formerly Basho Technologies

Stardog-Union

Initial release

2017

2015

2010

Current release

V0.10.20, January 2018

1.0.0, October 2023

3.0.0, September 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Erlang

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
OS X

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

yes, limited

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Native Erlang Interface

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

Clojure
Java
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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes, in Lua

yes

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes

selectable replication factor

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

links between datasets can be stored

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Access rights for users and roles

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