DBMS > Firebase Realtime Database vs. IBM Db2 Event Store vs. Oracle vs. PouchDB vs. SAP SQL Anywhere

System Properties Comparison Firebase Realtime Database vs. IBM Db2 Event Store vs. Oracle vs. PouchDB vs. SAP SQL Anywhere

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.

Distributed Event Store optimized for Internet of Things use cases

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store

Event Store
Time Series DBMS

Relational DBMS

Document 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	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.ibm.com/products/db2-event-store

www.oracle.com/database

pouchdb.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

firebase.google.com/docs/database

www.ibm.com/docs/en/db2-event-store

docs.oracle.com/en/database

pouchdb.com/guides

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

acquired by Google 2014

IBM

Oracle

Apache Software Foundation

SAP

formerly Sybase

Initial release

2012

2017

1980

2012

1992

Current release

2.0

23c, September 2023

7.1.1, June 2019

17, July 2015

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

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

C and C++

JavaScript

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

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

server-less, requires a JavaScript environment (browser, Node.js)

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

with proprietary extensions

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

JavaScript

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

yes, in C/C++, Java, .Net or Perl

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

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

yes

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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