DBMS > Apache Druid vs. Cubrid vs. Firebase Realtime Database vs. RocksDB

System Properties Comparison Apache Druid vs. Cubrid vs. Firebase Realtime Database vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Key-value store

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

druid.apache.org

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

firebase.google.com/products/realtime-database

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

cubrid.org/manuals

firebase.google.com/docs/database

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

CUBRID Corporation, CUBRID Foundation

Google

acquired by Google 2014

Facebook, Inc.

Initial release

2012

2008

2012

2013

Current release

29.0.1, April 2024

11.0, January 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Java

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

hosted

Linux

Data scheme

yes

schema-less columns are supported

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

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Java
JavaScript
Objective-C

C
C++
Go
Java
Perl
Python
Ruby

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

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

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

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.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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