DBMS > Cubrid vs. GeoMesa vs. HBase vs. Snowflake

System Properties Comparison Cubrid vs. GeoMesa vs. HBase vs. Snowflake

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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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

www.geomesa.org

hbase.apache.org

www.snowflake.com

Technical documentation

cubrid.org/manuals

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

hbase.apache.org/book.html

docs.snowflake.net/manuals/index.html

Developer

CUBRID Corporation, CUBRID Foundation

CCRi and others

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Snowflake Computing Inc.

Initial release

2008

2014

2008

2014

Current release

11.0, January 2021

5.0.0, May 2024

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache version 2

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

Scala

Java

Server operating systems

Linux
Windows

Linux
Unix
Windows

using Cygwin

hosted

Data scheme

yes

schema-free, schema definition possible

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
Thrift

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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.

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

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