DBMS > Citus vs. Hive vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. PostGIS

System Properties Comparison Citus vs. Hive vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Spatial DBMS

Secondary database models

Document store

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.citusdata.com

hive.apache.org

azure.microsoft.com/services/cosmos-db

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

postgis.net

Technical documentation

docs.citusdata.com

cwiki.apache.org/confluence/display/Hive/Home

learn.microsoft.com/azure/cosmos-db

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

postgis.net/documentation

Developer

Apache Software Foundation

initially developed by Facebook

Microsoft

Initial release

2010

2012

2014

1989

2005

Current release

8.1, December 2018

3.1.3, April 2022

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

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

Supported programming languages

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

C++
Java
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

user defined functions

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

yes

user defined functions and integration of map-reduce

JavaScript

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

user defined functions

Triggers

yes

JavaScript

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

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights for users, groups and roles

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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