DBMS > IRONdb vs. Transwarp StellarDB vs. Ultipa

System Properties Comparison IRONdb vs. Transwarp StellarDB vs. Ultipa

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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 distributed graph DBMS built for enterprise-level graph applications

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Time Series DBMS

Graph DBMS

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

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

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

www.transwarp.cn/en/product/stellardb

www.ultipa.com

Technical documentation

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

www.ultipa.com/document

Developer

Circonus LLC.

Transwarp

Ultipa

Initial release

2017

2019

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

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++

Server operating systems

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

HTTP API

OpenCypher

RESTful HTTP API

Supported programming languages

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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

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