DBMS > Amazon Redshift vs. FileMaker vs. Oracle vs. Rockset vs. Spark SQL

System Properties Comparison Amazon Redshift vs. FileMaker vs. Oracle vs. Rockset vs. Spark SQL

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.

Widely used RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS
Search engine

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	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

aws.amazon.com/redshift

www.claris.com/filemaker

www.oracle.com/database

rockset.com

spark.apache.org/sql

Technical documentation

docs.aws.amazon.com/redshift

www.claris.com/resources/documentation

docs.oracle.com/en/database

docs.rockset.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Amazon (based on PostgreSQL)

Claris

a subsidiary of Apple

Oracle

Rockset

Apache Software Foundation

Initial release

2012

1983

1980

2019

2014

Current release

19.4.1, November 2021

23c, September 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

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

C and C++

C++

Scala

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

hosted

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

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

yes

ingestion from XML files supported

Secondary indexes

restricted

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

via plugins

yes

with proprietary extensions

Read-only SQL queries, including JOINs

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

PHP

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Automatic sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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