DBMS > dBASE vs. FoundationDB vs. Google BigQuery vs. Splice Machine vs. Tigris

System Properties Comparison dBASE vs. FoundationDB vs. Google BigQuery vs. Splice Machine vs. Tigris

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

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.

Ordered key-value store. Core features are complimented by layers.

Large scale data warehouse service with append-only tables

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

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

Score	9.16
Rank	#43	Overall
	#27	Relational DBMS

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	0.05
Rank	#359	Overall
	#50	Document stores
	#52	Key-value stores
	#23	Search engines
	#37	Time Series DBMS

Website

www.dbase.com

github.com/apple/foundationdb

cloud.google.com/bigquery

splicemachine.com

www.tigrisdata.com

Technical documentation

www.dbase.com/support/knowledgebase

apple.github.io/foundationdb

cloud.google.com/bigquery/docs

splicemachine.com/how-it-works

www.tigrisdata.com/docs

Developer

Asthon Tate

FoundationDB

Google

Splice Machine

Tigris Data, Inc.

Initial release

1979

2013

2010

2014

2022

Current release

dBASE 2019, 2019

6.2.28, November 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Apache Version 2.0

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

C++

Java

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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.

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

dBase proprietary IDE

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

in SQL-layer only

user defined functions

in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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