DBMS > Amazon Redshift vs. FileMaker vs. Pinecone

System Properties Comparison Amazon Redshift vs. FileMaker vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A managed, cloud-native vector database

Primary database model

Relational DBMS

Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

aws.amazon.com/redshift

www.claris.com/filemaker

www.pinecone.io

Technical documentation

docs.aws.amazon.com/redshift

www.claris.com/resources/documentation

docs.pinecone.io/docs/overview

Developer

Amazon (based on PostgreSQL)

Claris

a subsidiary of Apple

Pinecone Systems, Inc

Initial release

2012

1983

2019

Current release

19.4.1, November 2021

License

Commercial or Open Source

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

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

yes

via plugins

APIs and other access methods

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

PHP

Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

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