DBMS > Cubrid vs. EJDB vs. GeoSpock vs. Postgres-XL

System Properties Comparison Cubrid vs. EJDB vs. GeoSpock vs. Postgres-XL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Spatial and temporal data processing engine for extreme data scale

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

Primary database model

Relational DBMS

Document store

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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

github.com/Softmotions/ejdb

geospock.com

www.postgres-xl.org

Technical documentation

cubrid.org/manuals

github.com/Softmotions/ejdb/blob/master/README.md

www.postgres-xl.org/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Softmotions

GeoSpock

Initial release

2008

2012

2014

since 2012, originally named StormDB

Current release

11.0, January 2021

2.0, September 2019

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

commercial

Open Source

Mozilla public license

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

C, C++, Java

Java, Javascript

Server operating systems

Linux
Windows

server-less

hosted

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

distributed, parallel query execution

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

in-process shared library

JDBC

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

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

NHN Willing to Be More Open
24 November 2008, 코리아타임스

provided by Google News

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

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

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

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

provided by Google News

Share this page