DBMS > Coveo vs. Interbase vs. MySQL vs. RavenDB vs. Realm

System Properties Comparison Coveo vs. Interbase vs. MySQL vs. RavenDB vs. Realm

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

Light-weight proven RDBMS

originally from Borland

Widely used open source RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

www.coveo.com

www.embarcadero.com/products/interbase

www.mysql.com

ravendb.net

realm.io

Technical documentation

docs.coveo.com

docs.embarcadero.com/products/interbase

dev.mysql.com/doc

ravendb.net/docs

realm.io/docs

Developer

Coveo

Embarcadero

Oracle

since 2010, originally MySQL AB, then Sun

Hibernating Rhinos

Realm, acquired by MongoDB in May 2019

Initial release

2012

1984

1995

2010

2014

Current release

InterBase 2020, December 2019

8.4.0, April 2024

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL version 3, commercial license available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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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++

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

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

yes

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.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
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#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

yes

proprietary syntax

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

yes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

In-Memory realm

User concepts

Access control

granular access controls, API key management, content filters

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

yes

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