DBMS > Cubrid vs. GeoSpock vs. GridGain vs. Snowflake

System Properties Comparison Cubrid vs. GeoSpock vs. GridGain vs. Snowflake

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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

Spatial and temporal data processing engine for extreme data scale

GridGain is an in-memory computing platform, built on Apache Ignite

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

Primary database model

Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

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

geospock.com

www.gridgain.com

www.snowflake.com

Technical documentation

cubrid.org/manuals

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

Developer

CUBRID Corporation, CUBRID Foundation

GeoSpock

GridGain Systems, Inc.

Snowflake Computing Inc.

Initial release

2008

2007

2014

Current release

11.0, January 2021

2.0, September 2019

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

commercial, open source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java, Javascript

Java, C++, .Net, Python, REST, SQL

Server operating systems

Linux
Windows

hosted

Linux
OS X
Solaris
Windows
z/OS

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

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

Role-based access control
Security Hooks for custom implementations

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

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