DBMS > Firebase Realtime Database vs. GridGain vs. Hypertable vs. NuoDB vs. Oracle

System Properties Comparison Firebase Realtime Database vs. GridGain vs. Hypertable vs. NuoDB vs. Oracle

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.

GridGain is an in-memory computing platform, built on Apache Ignite

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used RDBMS

Primary database model

Document store

Key-value store
Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.gridgain.com

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/database

Technical documentation

firebase.google.com/docs/database

www.gridgain.com/docs/index.html

doc.nuodb.com

docs.oracle.com/en/database

Developer

Google

acquired by Google 2014

GridGain Systems, Inc.

Hypertable Inc.

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Initial release

2012

2007

2009

2013

1980

Current release

GridGain 8.5.1

0.9.8.11, March 2016

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

limited edition free

commercial

restricted free version is 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

C++

C and C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

C++ API
Thrift

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes (compute grid and cache interceptors can be used instead)

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

Callbacks are triggered when data changes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor on file system level

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

can be realized in PL/SQL

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

tunable commit protocol

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

yes, based on authentication and database rules

Security Hooks for custom implementations

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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