DBMS > Ehcache vs. MarkLogic vs. Microsoft Azure AI Search

System Properties Comparison Ehcache vs. MarkLogic vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Operational and transactional Enterprise NoSQL database

Search-as-a-service for web and mobile app development

Primary database model

Key-value store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Search engine

Secondary database models

Vector DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

www.ehcache.org

www.marklogic.com

azure.microsoft.com/en-us/services/search

Technical documentation

www.ehcache.org/documentation

docs.marklogic.com

learn.microsoft.com/en-us/azure/search

Developer

Terracotta Inc, owned by Software AG

MarkLogic Corp.

Microsoft

Initial release

2009

2001

2015

Current release

3.10.0, March 2022

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

hosted

Data scheme

schema-free

Schema can be enforced

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

SQL

Support of SQL

yes

SQL92

APIs and other access methods

JCache

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

RESTful HTTP API

Supported programming languages

Java

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

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

Role-based access control at the document and subdocument levels

yes

using Azure authentication

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