DBMS > Firebase Realtime Database vs. Sadas Engine vs. Spark SQL vs. SQLite vs. STSdb

System Properties Comparison Firebase Realtime Database vs. Sadas Engine vs. Spark SQL vs. SQLite vs. STSdb

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Relational DBMS

Key-value store

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	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

firebase.google.com/products/realtime-database

www.sadasengine.com

spark.apache.org/sql

www.sqlite.org

github.com/STSSoft/STSdb4

Technical documentation

firebase.google.com/docs/database

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

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

Developer

Google

acquired by Google 2014

SADAS s.r.l.

Apache Software Foundation

Dwayne Richard Hipp

STS Soft SC

Initial release

2012

2006

2014

2000

2011

Current release

8.0

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPLv2, commercial license available

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++

Scala

Server operating systems

hosted

AIX
Linux
Windows

Linux
OS X
Windows

server-less

Windows

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

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API

Supported programming languages

Java
JavaScript
Objective-C

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

Java
Python
R
Scala

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#
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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