DBMS > Apache Druid vs. Firebase Realtime Database vs. PostgreSQL vs. TimesTen

System Properties Comparison Apache Druid vs. Firebase Realtime Database vs. PostgreSQL vs. TimesTen

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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.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

druid.apache.org

firebase.google.com/products/realtime-database

www.postgresql.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

druid.apache.org/docs/latest/design

firebase.google.com/docs/database

www.postgresql.org/docs

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation and contributors

Google

acquired by Google 2014

PostgreSQL Global Development Group

www.postgresql.org/developer

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

1989

1989: Postgres, 1996: PostgreSQL

1998

Current release

29.0.1, April 2024

16.3, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

More information provided by the system vendor

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