DBMS > Badger vs. mSQL vs. PostGIS vs. Postgres-XL vs. SAP SQL Anywhere

System Properties Comparison Badger vs. mSQL vs. PostGIS vs. Postgres-XL vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Spatial extension of PostgreSQL

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

github.com/dgraph-io/badger

hughestech.com.au/products/msql

postgis.net

www.postgres-xl.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

godoc.org/github.com/dgraph-io/badger

postgis.net/documentation

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

DGraph Labs

Hughes Technologies

SAP

formerly Sybase

Initial release

2017

1994

2005

2014

since 2012, originally named StormDB

1992

Current release

4.4, October 2021

3.4.2, February 2024

10 R1, October 2018

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

GPL v2.0

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

based on PostgreSQL

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on PostgreSQL

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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