DBMS > GeoMesa vs. Microsoft SQL Server vs. RethinkDB vs. SAP SQL Anywhere vs. XTDB

System Properties Comparison GeoMesa vs. Microsoft SQL Server vs. RethinkDB vs. SAP SQL Anywhere vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.geomesa.org

www.microsoft.com/en-us/sql-server

rethinkdb.com

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

rethinkdb.com/docs

help.sap.com/docs/SAP_SQL_Anywhere

www.xtdb.com/docs

Developer

CCRi and others

Microsoft

The Linux Foundation

since July 2017

SAP

formerly Sybase

Juxt Ltd.

Initial release

2014

1989

2009

1992

2019

Current release

5.0.0, May 2024

SQL Server 2022, November 2022

2.4.1, August 2020

17, July 2015

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

restricted free version is available

Open Source

Apache Version 2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Clojure

Server operating systems

Linux
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
HTTP API
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Clojure
Java

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

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

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

yes, each node contains all data

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

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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