DBMS > Firebase Realtime Database vs. Microsoft SQL Server vs. Sequoiadb vs. TimescaleDB vs. Warp 10

System Properties Comparison Firebase Realtime Database vs. Microsoft SQL Server vs. Sequoiadb vs. TimescaleDB vs. Warp 10

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.

Microsofts flagship relational DBMS

NewSQL database with distributed OLTP and SQL

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

firebase.google.com/products/realtime-database

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

www.sequoiadb.com

www.timescale.com

www.warp10.io

Technical documentation

firebase.google.com/docs/database

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

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.timescale.com

www.warp10.io/content/02_Getting_started

Developer

Google

acquired by Google 2014

Microsoft

Sequoiadb Ltd.

Timescale

SenX

Initial release

2012

1989

2013

2017

2015

Current release

SQL Server 2022, November 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache 2.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

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

proprietary protocol using JSON

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

HTTP API
Jupyter
WebSocket

Supported programming languages

Java
JavaScript
Objective-C

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

.Net
C++
Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
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

JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

WarpScript

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes, across time and space (hash partitioning) attributes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

Source-replica replication with hot standby and reads on replicas

selectable replication factor

based on HBase

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

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Document is locked during a transaction

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

simple password-based access control

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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