DBMS > Hive vs. Manticore Search vs. RDFox

System Properties Comparison Hive vs. Manticore Search vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Search engine

Graph DBMS
RDF store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Website

hive.apache.org

manticoresearch.com

www.oxfordsemantic.tech

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

manual.manticoresearch.com

docs.oxfordsemantic.tech

Developer

Apache Software Foundation

initially developed by Facebook

Manticore Software

Oxford Semantic Technologies

Initial release

2012

2017

Current release

3.1.3, April 2022

6.0, February 2023

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Linux
macOS
Windows

Data scheme

yes

Fixed schema

yes

RDF schemas

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

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

RESTful HTTP API
SPARQL 1.1

Supported programming languages

C++
Java
PHP
Python

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

C
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication based on Galera library

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

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 capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

Roles, resources, and access types

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