DBMS > FileMaker vs. InfluxDB vs. IRONdb vs. RDF4J vs. SQLite

System Properties Comparison FileMaker vs. InfluxDB vs. IRONdb vs. RDF4J vs. SQLite

Editorial information provided by DB-Engines

Name

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

Description

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

DBMS for storing time series, events and metrics

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.claris.com/filemaker

www.influxdata.com/products/influxdb-overview

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

rdf4j.org

www.sqlite.org

Technical documentation

www.claris.com/resources/documentation

docs.influxdata.com/influxdb

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

rdf4j.org/documentation

www.sqlite.org/docs.html

Developer

Claris

a subsidiary of Apple

Circonus LLC.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Dwayne Richard Hipp

Initial release

1983

2013

2017

2004

2000

Current release

19.4.1, November 2021

2.7.6, April 2024

V0.10.20, January 2018

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
OS X

through Homebrew

Linux

Linux
OS X
Unix
Windows

server-less

Data scheme

yes

schema-free

yes

RDF Schemas

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

text, numeric, histograms

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-like query language

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

yes

SQL-92 is not fully supported

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

HTTP API
JSON over UDP

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

PHP

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

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

Java
PHP
Python

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

selectable replication factor

in enterprise version only

configurable replication factor, datacenter aware

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

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

simple rights management via user accounts

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