DBMS > IRONdb vs. Oracle NoSQL vs. Percona Server for MongoDB vs. Spark SQL vs. SQLite

System Properties Comparison IRONdb vs. Oracle NoSQL vs. Percona Server for MongoDB 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 distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.oracle.com/database/nosql/technologies/nosql

www.percona.com/mongodb/software/percona-server-for-mongodb

spark.apache.org/sql

www.sqlite.org

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.percona.com/percona-distribution-for-mongodb

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

www.sqlite.org/docs.html

Developer

Circonus LLC.

Oracle

Percona

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2017

2011

2015

2014

2000

Current release

V0.10.20, January 2018

23.3, December 2023

3.4.10-2.10, November 2017

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL Version 2

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++

Java

C++

Scala

Server operating systems

Linux

Linux
Solaris SPARC/x86

Linux

Linux
OS X
Windows

server-less

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

optional

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.

Secondary indexes

yes

SQL

Support of SQL

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

HTTP API

RESTful HTTP API

proprietary protocol using JSON

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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
C#
Go
Java
JavaScript (Node.js)
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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, in Lua

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

via In-Memory Engine

yes

User concepts

Access control

Access rights for users and roles

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