DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Microsoft SQL Server vs. Oracle vs. Spark SQL vs. STSdb

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Microsoft SQL Server vs. Oracle vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Microsofts flagship relational DBMS

Widely used RDBMS

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.microsoft.com/en-us/sql-server

www.oracle.com/database

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/database

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

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Microsoft

Oracle

Apache Software Foundation

STS Soft SC

Initial release

2016

1989

1980

2014

2011

Current release

SQL Server 2022, November 2022

23c, September 2023

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

Scala

Server operating systems

hosted

Linux
Windows

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

Linux
OS X
Windows

Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

.NET Client API

Supported programming languages

C
Java
Perl
Python
R

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding, horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

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

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