DBMS > Firebase Realtime Database vs. Hazelcast vs. Linter vs. RocksDB vs. Tibero

System Properties Comparison Firebase Realtime Database vs. Hazelcast vs. Linter vs. RocksDB vs. Tibero

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

RDBMS for high security requirements

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

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

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

firebase.google.com/products/realtime-database

hazelcast.com

linter.ru

rocksdb.org

us.tmaxsoft.com/products/tibero

Technical documentation

firebase.google.com/docs/database

hazelcast.org/imdg/docs

github.com/facebook/rocksdb/wiki

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Google

acquired by Google 2014

Hazelcast

relex.ru

Facebook, Inc.

TmaxSoft

Initial release

2012

2008

1990

2013

2003

Current release

5.3.6, November 2023

8.11.4, April 2024

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

BSD

commercial

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

Java

C and C++

C++

C and Assembler

Server operating systems

hosted

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Java
JavaScript
Objective-C

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Event Listeners, Executor Services

yes

proprietary syntax with the possibility to convert from PL/SQL

Persistent Stored Procedure (PSM)

Triggers

Callbacks are triggered when data changes

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

one or two-phase-commit; repeatable reads; read commited

ACID

yes

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.

yes

planned for next version

User concepts

Access control

yes, based on authentication and database rules

Role-based access control

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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