DBMS > dBASE vs. GridGain vs. Snowflake vs. Teradata vs. Vitess

System Properties Comparison dBASE vs. GridGain vs. Snowflake vs. Teradata vs. Vitess

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Cloud-based data warehousing service for structured and semi-structured data

A hybrid cloud data analytics software platform (Teradata Vantage)

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

www.dbase.com/support/knowledgebase

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

docs.teradata.com

vitess.io/docs

Developer

Asthon Tate

GridGain Systems, Inc.

Snowflake Computing Inc.

Teradata

The Linux Foundation, PlanetScale

Initial release

1979

2007

2014

1984

2013

Current release

dBASE 2019, 2019

GridGain 8.5.1

Teradata Vantage 1.0 MU2, January 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Linux
OS X
Solaris
Windows

hosted

hosted
Linux

Docker
Linux
macOS

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL 2016 + extensions

yes

with proprietary extensions

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

dBase proprietary IDE

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

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

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

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes (compute grid and cache interceptors can be used instead)

user defined functions

yes

UDFs, stored procedures, table functions in parallel

yes

proprietary syntax

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Security Hooks for custom implementations

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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