DBMS > Manticore Search vs. PostgreSQL vs. RDF4J vs. RocksDB

System Properties Comparison Manticore Search vs. PostgreSQL vs. RDF4J vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

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

Primary database model

Search engine

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

RDF store

Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

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

Website

Technical documentation

manual.manticoresearch.com

www.postgresql.org/docs

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Manticore Software

PostgreSQL Global Development Group

www.postgresql.org/developer

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

Facebook, Inc.

Initial release

2017

1989

1989: Postgres, 1996: PostgreSQL

2004

2013

Current release

6.0, February 2023

16.3, May 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X
Unix
Windows

Linux

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

partitioning by range, list and (since PostgreSQL 11) by hash

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication

other methods possible by using 3rd party extensions

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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Speedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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