DBMS > Cubrid vs. Firebase Realtime Database vs. TerarkDB vs. XTDB

System Properties Comparison Cubrid vs. Firebase Realtime Database vs. TerarkDB vs. XTDB

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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-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

firebase.google.com/products/realtime-database

github.com/bytedance/terarkdb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/database

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.xtdb.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

Google

acquired by Google 2014

ByteDance, originally Terark

Juxt Ltd.

Initial release

2008

2012

2016

2019

Current release

11.0, January 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted open source version available

Open Source

MIT License

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++

Clojure

Server operating systems

Linux
Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Java API

HTTP REST
JDBC

Supported programming languages

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

Java
JavaScript
Objective-C

C++
Java

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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, based on authentication and database rules

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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