DBMS > MySQL vs. Oracle NoSQL vs. Spark SQL vs. Sphinx vs. STSdb

System Properties Comparison MySQL vs. Oracle NoSQL vs. Spark SQL vs. Sphinx vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Relational DBMS

Search engine

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.mysql.com

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

spark.apache.org/sql

sphinxsearch.com

github.com/STSSoft/STSdb4

Technical documentation

dev.mysql.com/doc

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

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

sphinxsearch.com/docs

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Apache Software Foundation

Sphinx Technologies Inc.

STS Soft SC

Initial release

1995

2011

2014

2001

2011

Current release

8.4.0, April 2024

24.1, May 2024

3.5.0 ( 2.13), September 2023

3.5.1, February 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

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

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Scala

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Windows

Data scheme

yes

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

yes

Typing

predefined data types such as float or date

yes

optional

yes

primitive types and user defined types (classes)

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

JDBC
ODBC

Proprietary protocol

.NET Client API

Supported programming languages

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

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

Java
Python
R
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

yes, utilizing Spark Core

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

none

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

Transaction concepts

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

ACID

not for MyISAM storage engine

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 Sphinx 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

Access rights for users and roles

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