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

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

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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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

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

janusgraph.org

www.kingbase.com.cn

Technical documentation

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

docs.janusgraph.org

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

Developer

Circonus LLC.

Linux Foundation; originally developed as Titan by Aurelius

BeiJing KINGBASE Information technologies inc.

Open Source, formerly Basho Technologies

Initial release

2017

1999

2015

Current release

V0.10.20, January 2018

1.0.0, October 2023

V8.0, August 2021

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

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 Java

Erlang

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

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

restricted

SQL

Support of SQL

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

Standard with numerous extensions

yes, limited

APIs and other access methods

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP API
Native Erlang Interface

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

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
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, in Lua

yes

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

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)

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes

selectable replication factor

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

links between datasets can be stored

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.

User concepts

Access control

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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