DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Citus vs. Microsoft SQL Server vs. SAP HANA vs. VictoriaMetrics

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Citus vs. Microsoft SQL Server vs. SAP HANA vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Microsofts flagship relational DBMS

In-memory, column based data store. Available as appliance or cloud service

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.citusdata.com

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

www.sap.com/products/hana.html

victoriametrics.com

Technical documentation

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

docs.citusdata.com

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

help.sap.com/hana

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Microsoft

SAP

VictoriaMetrics

Initial release

2016

2010

1989

2010

2018

Current release

8.1, December 2018

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

restricted free version is available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux

Linux
Windows

Appliance or cloud-service

FreeBSD
Linux
macOS
OpenBSD

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

yes

Secondary indexes

yes

SQL

Support of SQL

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
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

user defined functions

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

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

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

other methods possible by using 3rd party extensions

yes, but depending on the SQL-Server Edition

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

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

yes

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