DBMS > Cubrid vs. Google Cloud Bigtable vs. H2GIS vs. SpatiaLite

System Properties Comparison Cubrid vs. Google Cloud Bigtable vs. H2GIS vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Spatial extension of H2

Spatial extension of SQLite

Primary database model

Relational DBMS

Key-value store
Wide column store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

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

cloud.google.com/bigtable

www.h2gis.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

cubrid.org/manuals

cloud.google.com/bigtable/docs

www.h2gis.org/docs/home

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

CUBRID Corporation, CUBRID Foundation

Google

CNRS

Alessandro Furieri

Initial release

2008

2015

2013

2008

Current release

11.0, January 2021

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL 3.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++

Server operating systems

Linux
Windows

hosted

server-less

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

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

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

Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

based on H2

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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