DBMS > Cachelot.io vs. Firebase Realtime Database vs. Microsoft SQL Server vs. ReductStore

System Properties Comparison Cachelot.io vs. Firebase Realtime Database vs. Microsoft SQL Server vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

cachelot.io

firebase.google.com/products/realtime-database

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

github.com/reductstore
www.reduct.store

Technical documentation

firebase.google.com/docs/database

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

www.reduct.store/docs

Developer

Google

acquired by Google 2014

Microsoft

ReductStore LLC

Initial release

2015

2012

1989

2023

Current release

SQL Server 2022, November 2022

1.9, March 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

restricted free version is available

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C++, Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

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

yes

APIs and other access methods

Memcached protocol

Android
iOS
JavaScript API
RESTful HTTP API

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

HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Java
JavaScript
Objective-C

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

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

limited functionality with using 'rules'

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

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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