DBMS > GeoSpock vs. mSQL vs. Oracle Rdb vs. Postgres-XL vs. Spark SQL

System Properties Comparison GeoSpock vs. mSQL vs. Oracle Rdb vs. Postgres-XL vs. Spark SQL

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

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

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

geospock.com

hughestech.com.au/products/msql

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

www.postgres-xl.org

spark.apache.org/sql

Technical documentation

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

www.postgres-xl.org/documentation

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

Developer

GeoSpock

Hughes Technologies

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation

Initial release

1994

1984

2014

since 2012, originally named StormDB

2014

Current release

2.0, September 2019

4.4, October 2021

7.4.1.1, 2021

10 R1, October 2018

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free licenses can be provided

commercial

Open Source

Mozilla public license

Open Source

Apache 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, Javascript

Scala

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

HP Open VMS

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

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

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

SQL-like DML and DDL statements

APIs and other access methods

JDBC

JDBC
ODBC

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

JDBC
ODBC

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

MVCC

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.

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

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29 November 2018, diggers.news

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18 September 2020, The Register

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4 May 2013, oreilly.com

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