DBMS > Firebase Realtime Database vs. Greenplum vs. HBase vs. MySQL vs. Newts

System Properties Comparison Firebase Realtime Database vs. Greenplum vs. HBase vs. MySQL vs. Newts

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.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used open source RDBMS

Time Series DBMS based on Cassandra

Primary database model

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

firebase.google.com/products/realtime-database

greenplum.org

hbase.apache.org

www.mysql.com

opennms.github.io/newts

Technical documentation

firebase.google.com/docs/database

docs.greenplum.org

hbase.apache.org/book.html

dev.mysql.com/doc

github.com/OpenNMS/newts/wiki

Developer

Google

acquired by Google 2014

Pivotal Software Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

since 2010, originally MySQL AB, then Sun

OpenNMS Group

Initial release

2012

2005

2008

1995

2014

Current release

7.0.0, September 2023

2.3.4, January 2021

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

Linux

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
Java API

Supported programming languages

Java
JavaScript
Objective-C

C
Java
Perl
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Coprocessors in Java

yes

proprietary syntax

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

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

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

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