DBMS > H2GIS vs. Microsoft Azure Data Explorer vs. QuestDB vs. SpatiaLite vs. Yanza

System Properties Comparison H2GIS vs. Microsoft Azure Data Explorer vs. QuestDB vs. SpatiaLite vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Spatial extension of H2

Fully managed big data interactive analytics platform

A high performance open source SQL database for time series data

Spatial extension of SQLite

Time Series DBMS for IoT Applications

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	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.h2gis.org

azure.microsoft.com/services/data-explorer

questdb.io

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

yanza.com

Technical documentation

www.h2gis.org/docs/home

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

questdb.io/docs

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

Developer

CNRS

Microsoft

QuestDB Technology Inc

Alessandro Furieri

Yanza

Initial release

2013

2019

2014

2008

2015

Current release

cloud service with continuous releases

5.0.0, August 2020

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache 2.0

Open Source

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

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Java (Zero-GC), C++, Rust

C++

Server operating systems

hosted

Linux
macOS
Windows

server-less

Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free via InfluxDB Line Protocol

yes

schema-free

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

SQL with time-series extensions

yes

APIs and other access methods

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

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

HTTP API

Supported programming languages

Java

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

based on H2

Yes, possible languages: KQL, Python, R

Triggers

yes

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

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning (by timestamps)

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 with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID for single-table writes

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

through memory mapped files

yes

User concepts

Access control

yes

based on H2

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

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8 May 2024

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6 May 2024

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12 April 2024

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8 April 2024

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5 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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