DBMS > mSQL vs. OpenSearch vs. Oracle Rdb vs. Spark SQL vs. Sphinx

System Properties Comparison mSQL vs. OpenSearch vs. Oracle Rdb vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Primary database model

Secondary database models

Vector DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

hughestech.com.au/products/msql

github.com/opensearch-project
opensearch.org

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

spark.apache.org/sql

sphinxsearch.com

Technical documentation

opensearch.org/docs/latest

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

spark.apache.org/docs/latest/sql-programming-guide.html

sphinxsearch.com/docs

Developer

Hughes Technologies

Amazon Web Services

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation

Sphinx Technologies Inc.

Initial release

1994

2021

1984

2014

2001

Current release

4.4, October 2021

2.5.0, January 2023

7.4.1.1, 2021

3.5.0 ( 2.13), September 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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.

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Implementation language

Java

Scala

C++

Server operating systems

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

All OS with a Java VM

HP Open VMS

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

yes

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

JDBC
ODBC

Proprietary protocol

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Java
Python
R
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, utilizing Spark Core

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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 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

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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