DBMS > HyperSQL vs. Machbase Neo vs. Microsoft SQL Server vs. OceanBase vs. SAP SQL Anywhere

System Properties Comparison HyperSQL vs. Machbase Neo vs. Microsoft SQL Server vs. OceanBase vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

A distributed, high available RDBMS compatible with Oracle and MySQL

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Wide column store

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

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

hsqldb.org

machbase.com

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

en.oceanbase.com

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

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

machbase.com/dbms

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

en.oceanbase.com/docs/oceanbase-database

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Machbase

Microsoft

OceanBase

previously Alibaba and Ant Group

SAP

formerly Sybase

Initial release

2001

2013

1989

2010

1992

Current release

2.7.2, June 2023

V8.0, August 2023

SQL Server 2022, November 2022

4.3.0, April 2024

17, July 2015

License

Commercial or Open Source

Open Source

based on BSD license

commercial

free test version available

commercial

restricted free version is available

Open Source

Commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS
Windows

Linux
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

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

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

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

Server-side scripts

Stored procedures

Java, SQL

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

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes, but depending on the SQL-Server Edition

Multi-source replication using Paxos

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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