DBMS > dBASE vs. HEAVY.AI vs. Kinetica vs. Oracle vs. Sequoiadb

System Properties Comparison dBASE vs. HEAVY.AI vs. Kinetica vs. Oracle vs. Sequoiadb

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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Fully vectorized database across both GPUs and CPUs

Widely used RDBMS

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.dbase.com

github.com/heavyai/heavydb
www.heavy.ai

www.kinetica.com

www.oracle.com/database

www.sequoiadb.com

Technical documentation

www.dbase.com/support/knowledgebase

docs.heavy.ai

docs.kinetica.com

docs.oracle.com/en/database

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Asthon Tate

HEAVY.AI, Inc.

Kinetica

Oracle

Sequoiadb Ltd.

Initial release

1979

2016

2012

1980

2013

Current release

dBASE 2019, 2019

5.10, January 2022

7.1, August 2021

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

C, C++

C and C++

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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 DML and DDL statements

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

proprietary protocol using JSON

Supported programming languages

dBase proprietary IDE

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

PL/SQL

also stored procedures in Java possible

JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual 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

ACID

isolation level can be parameterized

Document is locked during a transaction

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

GPU vRAM or System RAM

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

simple password-based access control

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