DBMS > HBase vs. Microsoft SQL Server vs. MySQL vs. Oracle Berkeley DB vs. Teradata

System Properties Comparison HBase vs. Microsoft SQL Server vs. MySQL vs. Oracle Berkeley DB vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

Widely used open source RDBMS

Widely used in-process key-value store

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Wide column store

Relational DBMS

Key/Value like access via memcached API

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

hbase.apache.org

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

www.mysql.com

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

www.teradata.com

Technical documentation

hbase.apache.org/book.html

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

dev.mysql.com/doc

docs.oracle.com/cd/E17076_05/html/index.html

docs.teradata.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Teradata

Initial release

2008

1989

1995

1994

1984

Current release

2.3.4, January 2021

SQL Server 2022, November 2022

8.4.0, April 2024

18.1.40, May 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted
Linux

Data scheme

schema-free, schema definition possible

yes

schema-free

yes

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.

yes

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

yes

SQL 2016 + extensions

APIs and other access methods

Java API
RESTful HTTP API
Thrift

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

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication
Source-replica replication

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

not for MyISAM storage engine

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

not for MyISAM storage engine

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

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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