DBMS > Microsoft SQL Server vs. Percona Server for MongoDB vs. Solr vs. VoltDB

System Properties Comparison Microsoft SQL Server vs. Percona Server for MongoDB vs. Solr vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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	0.52
Rank	#254	Overall
	#39	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

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

www.percona.com/mongodb/software/percona-server-for-mongodb

solr.apache.org

www.voltdb.com

Technical documentation

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

docs.percona.com/percona-distribution-for-mongodb

solr.apache.org/resources.html

docs.voltdb.com

Developer

Microsoft

Percona

Apache Software Foundation

VoltDB Inc.

Initial release

1989

2015

2006

2010

Current release

SQL Server 2022, November 2022

3.4.10-2.10, November 2017

9.6.0, April 2024

11.3, April 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL Version 2

Open Source

Apache Version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Java, C++

Server operating systems

Linux
Windows

Linux

All OS with a Java VM

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

Linux
OS X

for development

Data scheme

yes

schema-free

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

only a subset of SQL 99

APIs and other access methods

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

proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

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

JavaScript

Java plugins

Java

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

optimistic locking

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

via In-Memory Engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

Users and roles with access to stored procedures

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