DBMS > GeoMesa vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison GeoMesa vs. Microsoft Azure Synapse Analytics vs. SAP SQL Anywhere vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Spatial DBMS

Relational DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.geomesa.org

azure.microsoft.com/services/synapse-analytics

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

www.snowflake.com

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

docs.microsoft.com/azure/synapse-analytics

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

CCRi and others

Microsoft

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2014

2016

1992

2014

Current release

4.0.5, February 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

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

Scala

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C#
Java
PHP

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Transact SQL

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

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding, horizontal partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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