DBMS > IRONdb vs. Kinetica vs. OrientDB vs. Snowflake vs. STSdb

System Properties Comparison IRONdb vs. Kinetica vs. OrientDB vs. Snowflake vs. STSdb

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

Fully vectorized database across both GPUs and CPUs

Multi-model DBMS (Document, Graph, Key/Value)

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

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

www.kinetica.com

orientdb.org

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

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

docs.kinetica.com

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

Developer

Circonus LLC.

Kinetica

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

STS Soft SC

Initial release

2017

2012

2010

2014

2011

Current release

V0.10.20, January 2018

7.1, August 2021

3.2.29, March 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C, C++

Java

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

hosted

Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

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

SQL-like DML and DDL statements

SQL-like query language, no joins

yes

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

.NET Client 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++
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

Java, Javascript

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Source-replica replication

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

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

In-memory capabilities

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

yes

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles on table level

Access rights for users and roles; record level security configurable

Users with fine-grained authorization concept, user roles and pluggable authentication

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