DBMS > DuckDB vs. Manticore Search vs. Postgres-XL vs. PostgreSQL

System Properties Comparison DuckDB vs. Manticore Search vs. Postgres-XL vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used open source RDBMS

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

Primary database model

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.

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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	4.68
Rank	#76	Overall
	#41	Relational DBMS

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	645.05
Rank	#4	Overall
	#4	Relational DBMS

Website

Technical documentation

duckdb.org/docs

manual.manticoresearch.com

www.postgres-xl.org/documentation

www.postgresql.org/docs

Developer

Manticore Software

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2018

2017

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

Current release

0.10, February 2024

6.0, February 2023

10 R1, October 2018

16.2, February 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

GPL version 2

Open Source

Mozilla public license

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Server operating systems

server-less

FreeBSD
Linux
macOS
Windows

Linux
macOS

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

Data scheme

yes

Fixed schema

yes

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

yes

XML type, but no XML query functionality

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

yes

SQL-like query language

yes

distributed, parallel query execution

yes

standard with numerous extensions

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

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

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

horizontal partitioning

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

Source-replica replication

other methods possible by using 3rd party extensions

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

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Conferences, events and webinars

more DBMS events

Monitoring PostgreSQL with Redgate Monitor
Webinar, 10-11am CT / 4-5pm BST, 22 May 2024

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