DBMS > FileMaker vs. Google BigQuery vs. NuoDB vs. Riak KV vs. TimesTen

System Properties Comparison FileMaker vs. Google BigQuery vs. NuoDB vs. Riak KV vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Distributed, fault tolerant key-value store

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key-value store

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

Relational DBMS

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

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

www.claris.com/filemaker

cloud.google.com/bigquery

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

doc.nuodb.com

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

docs.oracle.com/database/timesten-18.1

Developer

Claris

a subsidiary of Apple

Google

Dassault Systèmes

originally NuoDB, Inc.

OpenSource, formerly Basho Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1983

2010

2013

2009

1998

Current release

19.4.1, November 2021

3.2.0, December 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

Server operating systems

iOS

client part only
Linux
OS X
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Java, SQL

Erlang

PL/SQL

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

data is dynamically stored/cached on the nodes where it is read/written

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes

Managed transparently by NuoDB

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Standard SQL roles/ privileges, Administrative Users

yes, using Riak Security

fine grained access rights according to SQL-standard

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