DBMS > InterSystems IRIS vs. IRONdb vs. Prometheus vs. Spark SQL vs. SQLite

System Properties Comparison InterSystems IRIS vs. IRONdb vs. Prometheus vs. Spark SQL vs. SQLite

Editorial information provided by DB-Engines

Name

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

Description

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

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

Open-source Time Series DBMS and monitoring system

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.intersystems.com/products/intersystems-iris

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

prometheus.io

spark.apache.org/sql

www.sqlite.org

Technical documentation

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

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

prometheus.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

Developer

InterSystems

Circonus LLC.

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2018

2017

2015

2014

2000

Current release

2023.3, June 2023

V0.10.20, January 2018

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Public Domain

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++

Scala

Server operating systems

AIX
Linux
macOS
Ubuntu
Windows

Linux

Linux
Windows

Linux
OS X
Windows

server-less

Data scheme

depending on used data model

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

configurable replication factor, datacenter aware

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

User concepts

Access control

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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