DBMS > IRONdb vs. MySQL vs. Oracle Coherence vs. Spark SQL

System Properties Comparison IRONdb vs. MySQL vs. Oracle Coherence vs. Spark SQL

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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

Widely used open source RDBMS

Oracles in-memory data grid solution

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

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

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

www.mysql.com

www.oracle.com/java/coherence

spark.apache.org/sql

Technical documentation

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

dev.mysql.com/doc

docs.oracle.com/en/middleware/standalone/coherence

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

Developer

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Apache Software Foundation

Initial release

2017

1995

2007

2014

Current release

V0.10.20, January 2018

8.4.0, April 2024

14.1, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Scala

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

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

SQL

Support of SQL

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

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes, in Lua

yes

proprietary syntax

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

yes, with selectable consistency level

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

configurable

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optionally

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

Users with fine-grained authorization concept

no user groups or roles

authentification to access the cache via certificates or http basic authentication

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