DBMS > Cubrid vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. YottaDB

System Properties Comparison Cubrid vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. YottaDB

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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

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 fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store

Event Store
Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.20
Rank	#169	Overall
	#78	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	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

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

firebase.google.com/products/firestore

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

yottadb.com

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/firestore

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

yottadb.com/resources/documentation

Developer

CUBRID Corporation, CUBRID Foundation

Google

IBM

YottaDB, LLC

Initial release

2008

2017

2001

Current release

11.0, January 2021

2.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

AGPL 3.0

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

C and C++

Server operating systems

Linux
Windows

hosted

Linux

Linux, macOS, Windows for the developer addition

Docker
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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

by using the Octo plugin

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

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
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Active-active shard replication

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

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

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

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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