DBMS > Machbase Neo vs. Microsoft SQL Server vs. OrientDB vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison Machbase Neo vs. Microsoft SQL Server vs. OrientDB vs. SAP SQL Anywhere vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS
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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

machbase.com

www.microsoft.com/en-us/sql-server

orientdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

machbase.com/dbms

learn.microsoft.com/en-US/sql/sql-server

www.orientdb.com/docs/last/index.html

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

Machbase

Microsoft

OrientDB LTD; CallidusCloud; SAP

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2013

1989

2010

1992

2001

Current release

V8.0, August 2023

SQL Server 2022, November 2022

3.2.29, March 2024

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

commercial

free test version available

commercial

restricted free version is available

Open Source

Apache version 2

commercial

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++

Java

C++

Server operating systems

Linux
macOS
Windows

Linux
Windows

All OS with a Java JDK (>= JDK 6)

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language, no joins

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java, Javascript

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, but depending on the SQL-Server Edition

Multi-source replication

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

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.

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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