DBMS > Firebase Realtime Database vs. Kyligence Enterprise vs. MarkLogic vs. MySQL vs. SAP SQL Anywhere

System Properties Comparison Firebase Realtime Database vs. Kyligence Enterprise vs. MarkLogic vs. MySQL 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.

A distributed analytics engine for big data, built on top of Apache Kylin

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

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

Primary database model

Document store

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

firebase.google.com/products/realtime-database

kyligence.io/kyligence-enterprise

www.marklogic.com

www.mysql.com

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

Technical documentation

firebase.google.com/docs/database

docs.marklogic.com

dev.mysql.com/doc

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

acquired by Google 2014

Kyligence, Inc.

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Initial release

2012

2016

2001

1995

1992

Current release

11.0, December 2022

8.4.0, April 2024

17, July 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

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

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL92

yes

with proprietary extensions

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Java
JavaScript (Node.js)
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

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

via XQuery or JavaScript

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

ACID

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, with Range Indexes

yes

User concepts

Access control

yes, based on authentication and database rules

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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