DBMS > Machbase Neo vs. MySQL vs. Oracle Rdb vs. Sphinx vs. Stardog

System Properties Comparison Machbase Neo vs. MySQL vs. Oracle Rdb vs. Sphinx vs. Stardog

Editorial information provided by DB-Engines

Name

Description

TimeSeries DBMS for AIoT and BigData

Widely used open source RDBMS

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Search engine

Graph DBMS
RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

machbase.com

www.mysql.com

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

sphinxsearch.com

www.stardog.com

Technical documentation

machbase.com/dbms

dev.mysql.com/doc

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

sphinxsearch.com/docs

docs.stardog.com

Developer

Machbase

Oracle

since 2010, originally MySQL AB, then Sun

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sphinx Technologies Inc.

Stardog-Union

Initial release

2013

1995

1984

2001

2010

Current release

V8.0, August 2023

8.4.0, April 2024

7.4.1.1, 2021

3.5.1, February 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

free test version available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

GPL version 2, commercial licence available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

C++

Java

Server operating systems

Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

HP Open VMS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

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

yes

schema-free and OWL/RDFS-schema support

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.

yes

Import/export of XML data possible

Secondary indexes

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

Transaction concepts

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

ACID

not for MyISAM storage engine

yes, on a single node

ACID

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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