DBMS > Amazon Redshift vs. FileMaker vs. Firebase Realtime Database vs. Hypertable

System Properties Comparison Amazon Redshift vs. FileMaker vs. Firebase Realtime Database vs. Hypertable

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

An open source BigTable implementation based on distributed file systems such as Hadoop

Primary database model

Relational DBMS

Document store

Wide column store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Website

aws.amazon.com/redshift

www.claris.com/filemaker

firebase.google.com/products/realtime-database

Technical documentation

docs.aws.amazon.com/redshift

www.claris.com/resources/documentation

firebase.google.com/docs/database

Developer

Amazon (based on PostgreSQL)

Claris

a subsidiary of Apple

Google

acquired by Google 2014

Hypertable Inc.

Initial release

2012

1983

2012

2009

Current release

19.4.1, November 2021

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

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++

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

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

restricted

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

via plugins

APIs and other access methods

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

PHP

Java
JavaScript
Objective-C

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

selectable replication factor on file system level

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

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes, based on authentication and database rules

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