DBMS > dBASE vs. Dragonfly vs. IBM Cloudant vs. Microsoft SQL Server vs. Teradata

System Properties Comparison dBASE vs. Dragonfly vs. IBM Cloudant vs. Microsoft SQL Server vs. Teradata

Editorial information provided by DB-Engines

Name

Description

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Database as a Service offering based on Apache CouchDB

Microsofts flagship relational DBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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Trend Chart

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.dbase.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.ibm.com/products/cloudant

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

www.teradata.com

Technical documentation

www.dbase.com/support/knowledgebase

www.dragonflydb.io/docs

cloud.ibm.com/docs/Cloudant

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

docs.teradata.com

Developer

Asthon Tate

DragonflyDB team and community contributors

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Teradata

Initial release

1979

2023

2010

1989

1984

Current release

dBASE 2019, 2019

1.0, March 2023

SQL Server 2022, November 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

Erlang

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Linux

hosted

Linux
Windows

hosted
Linux

Data scheme

yes

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

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

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

Supported programming languages

dBase proprietary IDE

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

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

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

Lua

View functions (Map-Reduce) in JavaScript

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

publish/subscribe channels provide some trigger functionality

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

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Atomic execution of command blocks and scripts

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Optimistic locking

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 rights for users and roles

Password-based authentication

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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