DBMS > Coveo vs. MySQL vs. Oracle NoSQL vs. Typesense

System Properties Comparison Coveo vs. MySQL vs. Oracle NoSQL vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Widely used open source RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.76
Rank	#219	Overall
	#14	Search engines

Website

www.coveo.com

www.mysql.com

www.oracle.com/database/nosql/technologies/nosql

typesense.org

Technical documentation

docs.coveo.com

dev.mysql.com/doc

docs.oracle.com/en/database/other-databases/nosql-database/index.html

typesense.org/docs

Developer

Coveo

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Initial release

2012

1995

2011

2015

Current release

8.4.0, April 2024

24.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL V3

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Java

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Python

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

off heap cache

yes

User concepts

Access control

granular access controls, API key management, content filters

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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