DBMS > FileMaker vs. Google Cloud Bigtable vs. Lovefield vs. Riak TS

System Properties Comparison FileMaker vs. Google Cloud Bigtable vs. Lovefield vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Embeddable relational database for web apps written in pure JavaScript

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

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

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

www.claris.com/filemaker

cloud.google.com/bigtable

google.github.io/lovefield

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigtable/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

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

Developer

Claris

a subsidiary of Apple

Google

Open Source, formerly Basho Technologies

Initial release

1983

2015

2014

2015

Current release

19.4.1, November 2021

2.1.12, February 2017

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Erlang

Server operating systems

iOS

client part only
Linux
OS X
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

yes

via plugins

SQL-like query language

via JavaScript builder pattern

yes, limited

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Native Erlang Interface

Supported programming languages

PHP

C#
C++
Go
Java
JavaScript (Node.js)
Python

JavaScript

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

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Internal replication in Colossus, and regional replication between two clusters in different zones

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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