DBMS > Firebase Realtime Database vs. Sadas Engine vs. SAP IQ vs. SQLite vs. Teradata

System Properties Comparison Firebase Realtime Database vs. Sadas Engine vs. SAP IQ vs. SQLite vs. Teradata

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Columnar RDBMS optimized for Big Data analytics

Widely used embeddable, in-process RDBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.sadasengine.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.sqlite.org

www.teradata.com

Technical documentation

firebase.google.com/docs/database

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

help.sap.com/docs/SAP_IQ

www.sqlite.org/docs.html

docs.teradata.com

Developer

Google

acquired by Google 2014

SADAS s.r.l.

SAP, formerly Sybase

Dwayne Richard Hipp

Teradata

Initial release

2012

2006

1994

2000

1984

Current release

8.0

16.1 SPS04, April 2019

3.46.0 (23 May 2024), May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Public Domain

commercial

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.

Implementation language

C++

Server operating systems

hosted

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

server-less

hosted
Linux

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

SQL 2016 + extensions

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Java
JavaScript
Objective-C

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

UDFs, stored procedures, table functions in parallel

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

SAP/Sybase Replication Server

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

managed by 'Learn by Usage'

yes

User concepts

Access control

yes, based on authentication and database rules

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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