DBMS > CouchDB vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. PostGIS vs. SAP HANA

System Properties Comparison CouchDB vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. PostGIS vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Performant, highly scalable DBMS for AI and IoT applications

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Spatial extension of PostgreSQL

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

Primary database model

Document store

Key-value store
Vector DBMS

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational 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	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

couchdb.apache.org

www.jaguardb.com

azure.microsoft.com/services/synapse-analytics

postgis.net

www.sap.com/products/hana.html

Technical documentation

docs.couchdb.org/en/stable

www.jaguardb.com/support.html

docs.microsoft.com/azure/synapse-analytics

postgis.net/documentation

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

DataJaguar, Inc.

Microsoft

SAP

Initial release

2005

2015

2016

2005

2010

Current release

3.3.3, December 2023

3.3 July 2023

3.4.2, February 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPL V3.0

commercial

Open Source

GPL v2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

the server part. Clients available in other languages

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Appliance or cloud-service

Data scheme

schema-free

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

View functions in JavaScript

Transact SQL

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Sharding, horizontal partitioning

yes

based on PostgreSQL

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

based on PostgreSQL

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Access rights for users can be defined per database

rights management via user accounts

yes

based on PostgreSQL

yes

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