DBMS > H2GIS vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. SpatiaLite

System Properties Comparison H2GIS vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Fully managed big data interactive analytics platform

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Spatial extension of SQLite

Primary database model

column oriented

Secondary database models

Relational DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.h2gis.org

azure.microsoft.com/services/data-explorer

www.percona.com/mongodb/software/percona-server-for-mongodb

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

www.h2gis.org/docs/home

docs.microsoft.com/en-us/azure/data-explorer

docs.percona.com/percona-distribution-for-mongodb

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

CNRS

Microsoft

Percona

Alessandro Furieri

Initial release

2013

2019

2015

2008

Current release

cloud service with continuous releases

3.4.10-2.10, November 2017

5.0.0, August 2020

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

GPL Version 2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

Linux

server-less

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

Java

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes

based on H2

Yes, possible languages: KQL, Python, R

JavaScript

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate 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, multi-version concurrency control (MVCC)

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

via In-Memory Engine

yes

User concepts

Access control

yes

based on H2

Azure Active Directory Authentication

Access rights for users and roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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