DBMS > Manticore Search vs. MarkLogic vs. RDF4J vs. Realm vs. RocksDB

System Properties Comparison Manticore Search vs. MarkLogic vs. RDF4J vs. Realm vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Multi-storage database for search, including full-text search.

Operational and transactional Enterprise NoSQL database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

RDF store

Document store

Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

manual.manticoresearch.com

docs.marklogic.com

rdf4j.org/documentation

realm.io/docs

github.com/facebook/rocksdb/wiki

Developer

Manticore Software

MarkLogic Corp.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Realm, acquired by MongoDB in May 2019

Facebook, Inc.

Initial release

2017

2001

2004

2014

2013

Current release

6.0, February 2023

11.0, December 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

GPL version 2

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

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

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

Fixed schema

schema-free

Schema can be enforced

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL92

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Java
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

none

yes

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

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

ACID

Isolation support depends on the API used

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

in-memory storage is supported as well

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

In-Memory realm

yes

User concepts

Access control

Role-based access control at the document and subdocument levels

yes

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