DBMS > Apache Druid vs. Firebase Realtime Database vs. Microsoft SQL Server vs. MySQL vs. PostGIS

System Properties Comparison Apache Druid vs. Firebase Realtime Database vs. Microsoft SQL Server vs. MySQL vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Microsofts flagship relational DBMS

Widely used open source RDBMS

Spatial extension of PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Website

druid.apache.org

firebase.google.com/products/realtime-database

www.microsoft.com/en-us/sql-server

www.mysql.com

postgis.net

Technical documentation

druid.apache.org/docs/latest/design

firebase.google.com/docs/database

learn.microsoft.com/en-US/sql/sql-server

dev.mysql.com/doc

postgis.net/documentation

Developer

Apache Software Foundation and contributors

Google

acquired by Google 2014

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

1989

1995

2005

Current release

30.0.0, June 2024

SQL Server 2022, November 2022

9.0.0, July 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
OS X
Unix

hosted

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
JavaScript
Objective-C

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

proprietary syntax

user defined functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

based on PostgreSQL

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