DBMS > Apache Spark (SQL) vs. PostgreSQL vs. Raima Database Manager

System Properties Comparison Apache Spark (SQL) vs. PostgreSQL vs. Raima Database Manager

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Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

RDBMS with a small footprint, either embedded into an application or used as a database server

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS
Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	21.62
Rank	#29	Overall
	#18	Relational DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	0.27
Rank	#289	Overall
	#129	Relational DBMS
	#22	Time Series DBMS

Website

spark.apache.org/sql

www.postgresql.org

raima.com

Technical documentation

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

www.postgresql.org/docs

docs.raima.com

Developer

Apache Software Foundation

PostgreSQL Global Development Group

www.postgresql.org/developer

Raima Inc.

Initial release

2014

1989

1989: Postgres, 1996: PostgreSQL

1984

Current release

3.5.0 ( 2.13), September 2023

16.4, August 2024

15, June 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Scala

Server operating systems

Linux
OS X
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

Data scheme

yes

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

specific XML-type available, but no XML query functionality.

Exporting/Importing of XML structures possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python
R
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Objective-C
PL/SQL

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

partitioning by range, list and (since PostgreSQL 11) by hash

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

More information provided by the system vendor

News

RaimaDB and QNX Forge a Powerful Partnership in Embedded Systems
9 July 2024

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

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