DBMS > Elasticsearch vs. Firebase Realtime Database vs. Graph Engine vs. Oracle vs. Trafodion

System Properties Comparison Elasticsearch vs. Firebase Realtime Database vs. Graph Engine vs. Oracle vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Widely used RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Search engine

Document store

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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	135.35
Rank	#7	Overall
	#1	Search engines

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.elastic.co/elasticsearch

firebase.google.com/products/realtime-database

www.graphengine.io

www.oracle.com/database

trafodion.apache.org

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

firebase.google.com/docs/database

www.graphengine.io/docs/manual

docs.oracle.com/en/database

trafodion.apache.org/documentation.html

Developer

Elastic

Google

acquired by Google 2014

Microsoft

Oracle

Apache Software Foundation, originally developed by HP

Initial release

2010

2012

2010

1980

2014

Current release

8.6, January 2023

23c, September 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

MIT License

commercial

restricted free version is available

Open Source

Apache 2.0

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

.NET and C

C and C++

C++, Java

Server operating systems

All OS with a Java VM

hosted

.NET

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

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

Schemaless in JSON and XML columns

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

C#
C++
F#
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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

yes

PL/SQL

also stored procedures in Java possible

Java Stored Procedures

Triggers

yes

by using the 'percolation' feature

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

can be realized in PL/SQL

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

Memcached and Redis integration

yes

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

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.