DBMS > Apache Spark (SQL) vs. Dolt vs. Galaxybase vs. PostgreSQL

System Properties Comparison Apache Spark (SQL) vs. Dolt vs. Galaxybase vs. PostgreSQL

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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

A MySQL compatible DBMS with Git-like versioning of data and schema

Scalable, ACID-compliant native distributed parallel graph platform

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

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

Secondary database models

Document store

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	0.60
Rank	#232	Overall
	#106	Relational DBMS

Score	0.00
Rank	#385	Overall
	#41	Graph DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

spark.apache.org/sql

github.com/dolthub/dolt
www.dolthub.com

galaxybase.com

www.postgresql.org

Technical documentation

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

docs.dolthub.com

www.postgresql.org/docs

Developer

Apache Software Foundation

DoltHub Inc

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2014

2018

2017

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.5.0 ( 2.13), September 2023

Nov 20, November 2021

16.4, August 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Scala

C and Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

Linux

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

Data scheme

yes

Strong typed schema

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

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

Supported programming languages

Java
Python
R
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined procedures and functions

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Source-replica replication

other methods possible by using 3rd party extensions

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

Relationships in graphs

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

Only one user is configurable, and must be specified in the config file at startup

Role-based access control

fine grained access rights according to SQL-standard

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