DBMS > Linter vs. Manticore Search vs. Oracle Rdb vs. Riak KV vs. Sphinx

System Properties Comparison Linter vs. Manticore Search vs. Oracle Rdb vs. Riak KV vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

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

Distributed, fault tolerant key-value store

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Search engine

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

linter.ru

manticoresearch.com

www.oracle.com/database/technologies/related/rdb.html

sphinxsearch.com

Technical documentation

manual.manticoresearch.com

www.oracle.com/database/technologies/related/rdb-doc.html

www.tiot.jp/riak-docs/riak/kv/latest

sphinxsearch.com/docs

Developer

relex.ru

Manticore Software

Oracle, originally developed by Digital Equipment Corporation (DEC)

OpenSource, formerly Basho Technologies

Sphinx Technologies Inc.

Initial release

1990

2017

1984

2009

2001

Current release

6.0, February 2023

7.4.1.1, 2021

3.2.0, December 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL version 2, commercial licence available

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.

Implementation language

C and C++

C++

Erlang

C++

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
macOS
Windows

HP Open VMS

Linux
OS X

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Fixed schema

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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

Secondary indexes

yes

full-text index on all search fields

yes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

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

HTTP API
Native Erlang Interface

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

no "single point of failure"

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication based on Galera library

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

yes, on a single node

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

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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