DBMS > Firebase Realtime Database vs. GigaSpaces vs. HarperDB vs. Hypertable vs. MySQL

System Properties Comparison Firebase Realtime Database vs. GigaSpaces vs. HarperDB vs. Hypertable vs. MySQL

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

An open source BigTable implementation based on distributed file systems such as Hadoop

Widely used open source RDBMS

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Document store

Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.gigaspaces.com

www.harperdb.io

www.mysql.com

Technical documentation

firebase.google.com/docs/database

docs.gigaspaces.com/latest/landing.html

docs.harperdb.io/docs

dev.mysql.com/doc

Developer

Google

acquired by Google 2014

Gigaspaces Technologies

HarperDB

Hypertable Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2000

2017

2009

1995

Current release

15.5, September 2020

3.1, August 2021

0.9.8.11, March 2016

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

free community edition available

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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++, .Net

Node.js

C++

C and C++

Server operating systems

hosted

Linux
macOS
Solaris
Windows

Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like data manipulation statements

yes

with proprietary extensions

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
JavaScript
Objective-C

.Net
C++
Java
Python
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Custom Functions

since release 3.1

yes

proprietary syntax

Triggers

Callbacks are triggered when data changes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

the nodes on which a table resides can be defined

selectable replication factor on file system level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

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

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

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

Atomic execution of specific operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, using LMDB

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

Role-based access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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