DBMS > Cubrid vs. GBase vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. SWC-DB

System Properties Comparison Cubrid vs. GBase vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Distributed Event Store optimized for Internet of Things use cases

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store

Event Store
Time Series DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

www.gbase.cn

firebase.google.com/products/firestore

www.ibm.com/products/db2-event-store

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/firestore

www.ibm.com/docs/en/db2-event-store

Developer

CUBRID Corporation, CUBRID Foundation

General Data Technology Co., Ltd.

Google

IBM

Alex Kashirin

Initial release

2008

2004

2017

2020

Current release

11.0, January 2021

GBase 8a, GBase 8s, GBase 8c

2.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

GPL V3

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

C, Java, Python

C and C++

C++

Server operating systems

Linux
Windows

Linux

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

yes

schema-free

yes

schema-free

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

SQL

Support of SQL

yes

Standard with numerous extensions

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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