DBMS > dBASE vs. IBM Db2 Event Store vs. KeyDB vs. Microsoft SQL Server vs. Teradata

System Properties Comparison dBASE vs. IBM Db2 Event Store vs. KeyDB 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.

Distributed Event Store optimized for Internet of Things use cases

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsofts flagship relational DBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.dbase.com

www.ibm.com/products/db2-event-store

github.com/Snapchat/KeyDB
keydb.dev

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

www.teradata.com

Technical documentation

www.dbase.com/support/knowledgebase

www.ibm.com/docs/en/db2-event-store

docs.keydb.dev

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

docs.teradata.com

Developer

Asthon Tate

IBM

EQ Alpha Technology Ltd.

Microsoft

Teradata

Initial release

1979

2017

2019

1989

1984

Current release

dBASE 2019, 2019

2.0

SQL Server 2022, November 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

BSD-3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C and C++

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
Windows

hosted
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

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

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL 2016 + extensions

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

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++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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.

yes

Lua

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

yes

UDFs, stored procedures, table functions in parallel

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

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard 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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

fine grained access rights according to SQL-standard

simple password-based access control and ACL

fine grained access rights according to SQL-standard

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