DBMS > Amazon Redshift vs. BigObject vs. FileMaker vs. Oracle NoSQL

System Properties Comparison Amazon Redshift vs. BigObject vs. FileMaker vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

www.claris.com/filemaker

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

www.claris.com/resources/documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Claris

a subsidiary of Apple

Oracle

Initial release

2012

2015

1983

2011

Current release

19.4.1, November 2021

23.3, December 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

iOS

client part only
Linux
OS X
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

via plugins

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

PHP

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

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication, warm standby

since Version 14

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access rights for users and roles

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