DBMS > FileMaker vs. InterSystems IRIS vs. Oracle vs. Solr

System Properties Comparison FileMaker vs. InterSystems IRIS vs. Oracle vs. Solr

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Editorial information provided by DB-Engines

Name

Description

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

Widely used RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	4.39
Rank	#81	Overall
	#13	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#44	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	44.28
Rank	#24	Overall
	#3	Search engines

Website

www.claris.com/filemaker

www.intersystems.com/products/intersystems-iris

www.oracle.com/database

solr.apache.org

Technical documentation

www.claris.com/resources/documentation

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

docs.oracle.com/en/database

solr.apache.org/resources.html

Developer

Claris

a subsidiary of Apple

InterSystems

Oracle

Apache Software Foundation

Initial release

1983

2018

1980

2006

Current release

19.4.1, November 2021

2023.3, June 2023

23c, September 2023

9.5.0, February 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2

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

Server operating systems

iOS

client part only
Linux
OS X
Windows

AIX
Linux
macOS
Ubuntu
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

depending on used data model

yes

Schemaless in JSON and XML columns

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

via plugins

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

Supported programming languages

PHP

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

optimistic locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

simple rights management via user accounts and connection to external directory services

yes

fine grained access rights according to SQL-standard

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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