DBMS > Manticore Search vs. MySQL vs. OpenEdge vs. Oracle NoSQL

System Properties Comparison Manticore Search vs. MySQL vs. OpenEdge vs. Oracle NoSQL

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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

Application development environment with integrated database management system

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

manticoresearch.com

www.mysql.com

www.progress.com/openedge

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

manual.manticoresearch.com

dev.mysql.com/doc

documentation.progress.com/output/ua/OpenEdge_latest

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Progress Software Corporation

Oracle

Initial release

2017

1995

1984

2011

Current release

6.0, February 2023

8.4.0, April 2024

OpenEdge 12.2, March 2020

23.3, December 2023

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and C++

Java

Server operating systems

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
Solaris SPARC/x86

Data scheme

Fixed schema

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

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

yes

optional

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

close to SQL 92

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Progress proprietary ABL (Advanced Business Language)

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

not for MyISAM storage engine

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

off heap cache

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Users and groups

Access rights for users and roles

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