DBMS > Blueflood vs. Microsoft SQL Server vs. PouchDB vs. SQL.JS vs. TDSQL for MySQL

System Properties Comparison Blueflood vs. Microsoft SQL Server vs. PouchDB vs. SQL.JS vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Port of SQLite to JavaScript

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	0.57
Rank	#248	Overall
	#114	Relational DBMS

Score	0.82
Rank	#213	Overall
	#97	Relational DBMS

Website

blueflood.io

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

pouchdb.com

sql.js.org

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/rax-maas/blueflood/wiki

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

pouchdb.com/guides

sql.js.org/documentation/index.html

www.tencentcloud.com/document/product/1042

Developer

Rackspace

Microsoft

Apache Software Foundation

Alon Zakai

enhancements implemented by others

Tencent

Initial release

2013

1989

2012

2013

Current release

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

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

Java

C++

JavaScript

Server operating systems

Linux
OS X

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Data scheme

predefined scheme

yes

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

via views

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST

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

HTTP REST

only for PouchDB Server
JavaScript API

JavaScript API

JDBC
ODBC

Supported programming languages

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

JavaScript

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

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

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

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

Sharding

with a proxy-based framework, named couchdb-lounge

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

except by serializing a db to a file

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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