DBMS > Elasticsearch vs. MySQL vs. NuoDB vs. Oracle vs. Prometheus

System Properties Comparison Elasticsearch vs. MySQL vs. NuoDB vs. Oracle vs. Prometheus

Editorial information provided by DB-Engines

Name

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

Widely used open source RDBMS

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

Widely used RDBMS

Open-source Time Series DBMS and monitoring system

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial 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	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

www.elastic.co/elasticsearch

www.mysql.com

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

www.oracle.com/database

prometheus.io

Technical documentation

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

dev.mysql.com/doc

doc.nuodb.com

docs.oracle.com/en/database

prometheus.io/docs

Developer

Elastic

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Initial release

2010

1995

2013

1980

2015

Current release

8.6, January 2023

8.4.0, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

Elastic License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C and C++

C++

C and C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

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

Linux
Windows

Data scheme

schema-free

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

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP/JSON API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
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

.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

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

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

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

Multi-source replication
Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

can be realized in PL/SQL

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

Immediate Consistency

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

Memcached and Redis integration

yes

Temporary table

yes

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

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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