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

System Properties Comparison Blueflood vs. Microsoft SQL Server vs. Solr 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

A widely used distributed, scalable search engine based on Apache Lucene

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

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	44.28
Rank	#24	Overall
	#3	Search engines

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

solr.apache.org

sql.js.org

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/rax-maas/blueflood/wiki

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

solr.apache.org/resources.html

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

2006

2012

2013

Current release

SQL Server 2022, November 2022

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2

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++

Java

JavaScript

Server operating systems

Linux
OS X

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

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

hosted

Data scheme

predefined scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

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)

Java API
RESTful HTTP/JSON API

JavaScript API

JDBC
ODBC

Supported programming languages

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

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

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

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

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

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

Users with fine-grained authorization concept

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