DBMS > FileMaker vs. IRONdb vs. RDF4J vs. Riak KV vs. Sqrrl

System Properties Comparison FileMaker vs. IRONdb vs. RDF4J vs. Riak KV vs. Sqrrl

Editorial information provided by DB-Engines

Name

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

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

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.

Distributed, fault tolerant key-value store

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

www.claris.com/filemaker

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

rdf4j.org

sqrrl.com

Technical documentation

www.claris.com/resources/documentation

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

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Claris

a subsidiary of Apple

Circonus LLC.

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

OpenSource, formerly Basho Technologies

Amazon

originally Sqrrl Data, Inc.

Initial release

1983

2017

2004

2009

2012

Current release

19.4.1, November 2021

V0.10.20, January 2018

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

commercial

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

Erlang

Java

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux

Linux
OS X
Unix
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

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

A http query request can return the data in XML format

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

via plugins

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

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

PHP

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

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

yes, in Lua

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

none

Sharding

no "single point of failure"

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

configurable replication factor, datacenter aware

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Isolation support depends on the API used

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

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

yes, using Riak Security

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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