DBMS > Manticore Search vs. RDF4J vs. Riak KV vs. searchxml

System Properties Comparison Manticore Search vs. RDF4J vs. Riak KV vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

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

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

Distributed, fault tolerant key-value store

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Search engine

RDF store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Native XML DBMS
Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

manticoresearch.com

rdf4j.org

www.searchxml.net/category/products

Technical documentation

manual.manticoresearch.com

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

www.searchxml.net/support/handouts

Developer

Manticore Software

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

OpenSource, formerly Basho Technologies

informationpartners gmbh

Initial release

2017

2004

2009

2015

Current release

6.0, February 2023

3.2.0, December 2022

1.0

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

commercial

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

Erlang

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Linux
OS X

Windows

Data scheme

Fixed schema

yes

RDF Schemas

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

restricted

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

yes

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

none

selectable replication factor

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

Isolation support depends on the API used

multiple readers, single writer

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.

User concepts

Access control

yes, using Riak Security

Domain, group and role-based access control at the document level and for application services

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