DBMS > HBase vs. Interbase vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenQM

System Properties Comparison HBase vs. Interbase vs. Microsoft Azure Table Storage vs. Microsoft SQL Server vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Light-weight proven RDBMS

originally from Borland

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

hbase.apache.org

www.embarcadero.com/products/interbase

azure.microsoft.com/en-us/services/storage/tables

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

hbase.apache.org/book.html

docs.embarcadero.com/products/interbase

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Embarcadero

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2008

1984

2012

1989

1993

Current release

2.3.4, January 2021

InterBase 2020, December 2019

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Android
iOS
Linux
OS X
Windows

hosted

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

with some exceptions

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

RESTful HTTP API

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

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

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

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Interbase procedure and trigger language

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Interbase Change Views

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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