DBMS > Faircom DB vs. Manticore Search vs. PostgreSQL vs. Solr vs. Stardog

System Properties Comparison Faircom DB vs. Manticore Search vs. PostgreSQL vs. Solr vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

A widely used distributed, scalable search engine based on Apache Lucene

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store
Relational DBMS

Search engine

Relational DBMS

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

Search engine

Graph DBMS
RDF 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

Spatial DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.faircom.com/products/faircom-db

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

manual.manticoresearch.com

www.postgresql.org/docs

solr.apache.org/resources.html

docs.stardog.com

Developer

FairCom Corporation

Manticore Software

PostgreSQL Global Development Group

www.postgresql.org/developer

Apache Software Foundation

Stardog-Union

Initial release

1979

2017

1989

1989: Postgres, 1996: PostgreSQL

2006

2010

Current release

V12, November 2020

6.0, February 2023

16.3, May 2024

9.6.0, April 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

GPL version 2

Open Source

BSD

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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.

Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.

Implementation language

ANSI C, C++

C++

Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

FreeBSD
Linux
macOS
Windows

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

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
macOS
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

Fixed schema

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

yes

supports customizable data types and automatic typing

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.

yes

Import/export of XML data possible

Secondary indexes

yes

full-text index on all search fields

yes

All search fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language

yes

standard with numerous extensions

Solr Parallel SQL Interface

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

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

Java plugins

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

User configurable commands triggered on index changes

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

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

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Synchronous replication based on Galera library

Source-replica replication

other methods possible by using 3rd party extensions

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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