DBMS > MarkLogic vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Solr

System Properties Comparison MarkLogic vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Solr

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Editorial information provided by DB-Engines

Name

Description

Operational and transactional Enterprise NoSQL database

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

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

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.marklogic.com

azure.microsoft.com/services/synapse-analytics

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

solr.apache.org

Technical documentation

docs.marklogic.com

docs.microsoft.com/azure/synapse-analytics

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

solr.apache.org/resources.html

Developer

MarkLogic Corp.

Microsoft

Apache Software Foundation

Initial release

2001

2016

1989

2006

Current release

11.0, December 2022

SQL Server 2022, November 2022

9.6.0, April 2024

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache Version 2

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

C++

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

All OS with a Java VM

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

Data scheme

schema-free

Schema can be enforced

yes

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

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

SQL

Support of SQL

yes

SQL92

yes

Solr Parallel SQL Interface

APIs and other access methods

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC

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

Java API
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java
PHP

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Transact SQL

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

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

optimistic locking

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, with Range Indexes

yes

User concepts

Access control

Role-based access control at the document and subdocument levels

yes

fine grained access rights according to SQL-standard

yes

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