DBMS > Microsoft SQL Server vs. mSQL vs. OrigoDB vs. Solr vs. WakandaDB

System Properties Comparison Microsoft SQL Server vs. mSQL vs. OrigoDB vs. Solr vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Search engine

Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

hughestech.com.au/products/msql

origodb.com

solr.apache.org

wakanda.github.io

Technical documentation

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

origodb.com/docs

solr.apache.org/resources.html

wakanda.github.io/doc

Developer

Microsoft

Hughes Technologies

Robert Friberg et al

Apache Software Foundation

Wakanda SAS

Initial release

1989

1994

2009

under the name LiveDB

2006

2012

Current release

SQL Server 2022, November 2022

4.4, October 2021

9.6.0, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++, JavaScript

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

All OS with a Java VM

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

Linux
OS X
Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

Solr Parallel SQL Interface

APIs and other access methods

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

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

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

JavaScript

Server-side scripts

Stored procedures

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

yes

Java plugins

yes

Triggers

yes

Domain Events

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

Source-replica replication

yes

none

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

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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

Role based authorization

yes

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