DBMS > H2GIS vs. Microsoft Azure Cosmos DB vs. Spark SQL vs. STSdb vs. Valentina Server

System Properties Comparison H2GIS vs. Microsoft Azure Cosmos DB vs. Spark SQL vs. STSdb vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Globally distributed, horizontally scalable, multi-model database service

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Object-relational database and reports server

Primary database model

Spatial DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.h2gis.org

azure.microsoft.com/services/cosmos-db

spark.apache.org/sql

github.com/STSSoft/STSdb4

www.valentina-db.net

Technical documentation

www.h2gis.org/docs/home

learn.microsoft.com/azure/cosmos-db

spark.apache.org/docs/latest/sql-programming-guide.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

CNRS

Microsoft

Apache Software Foundation

STS Soft SC

Paradigma Software

Initial release

2013

2014

2011

1999

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

5.7.5

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

commercial

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

Scala

Server operating systems

hosted

Linux
OS X
Windows

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

.NET Client API

ODBC

Supported programming languages

Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java
Python
R
Scala

C#
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

based on H2

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

yes

based on H2

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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