DBMS > GeoMesa vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Riak TS

System Properties Comparison GeoMesa vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Riak TS

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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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Spatial DBMS

Relational DBMS

Time Series DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

www.geomesa.org

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

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

docs.microsoft.com/azure/synapse-analytics

www.oracle.com/database/technologies/related/rdb-doc.html

www.tiot.jp/riak-docs/riak/ts/latest

Developer

CCRi and others

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Open Source, formerly Basho Technologies

Initial release

2014

2016

1984

2015

Current release

5.0.0, May 2024

7.4.1.1, 2021

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

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++

Erlang

Server operating systems

hosted

HP Open VMS

Linux
OS X

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C#
Java
PHP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Transact SQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

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

yes

links between datasets can be stored

Transaction concepts

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

ACID

yes, on a single node

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

User concepts

Access control

yes

depending on the DBMS used for storage

yes

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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