DBMS > H2 vs. Microsoft Azure SQL Database vs. Postgres-XL vs. VictoriaMetrics

System Properties Comparison H2 vs. Microsoft Azure SQL Database vs. Postgres-XL vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Database as a Service offering with high compatibility to Microsoft SQL Server

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

www.h2database.com

azure.microsoft.com/en-us/products/azure-sql/database

www.postgres-xl.org

victoriametrics.com

Technical documentation

www.h2database.com/html/main.html

docs.microsoft.com/en-us/azure/azure-sql

www.postgres-xl.org/documentation

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Thomas Mueller

Microsoft

VictoriaMetrics

Initial release

2005

2010

2014

since 2012, originally named StormDB

2018

Current release

2.2.220, July 2023

V12

10 R1, October 2018

v1.91, May 2023

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Mozilla public license

Open Source

Apache Version 2.0

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

All OS with a Java VM

hosted

Linux
macOS

FreeBSD
Linux
macOS
OpenBSD

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Transact SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, with always 3 replicas available

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

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