DBMS > Apache Drill vs. dBASE vs. FileMaker vs. Google BigQuery vs. Splice Machine

System Properties Comparison Apache Drill vs. dBASE vs. FileMaker vs. Google BigQuery vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

Primary database model

Document store
Relational DBMS

Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	9.16
Rank	#43	Overall
	#27	Relational DBMS

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

drill.apache.org

www.dbase.com

www.claris.com/filemaker

cloud.google.com/bigquery

splicemachine.com

Technical documentation

drill.apache.org/docs

www.dbase.com/support/knowledgebase

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Asthon Tate

Claris

a subsidiary of Apple

Google

Splice Machine

Initial release

2012

1979

1983

2010

2014

Current release

1.20.3, January 2023

dBASE 2019, 2019

19.4.1, November 2021

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL 3.0, commercial license 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

Server operating systems

Linux
OS X
Windows

DOS

dBase Classic
Windows

dBase Pro

iOS

client part only
Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

via plugins

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C++

dBase proprietary IDE

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

The IDE can access stored procedures in other database systems.

yes

user defined functions

in JavaScript

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication, warm standby

since Version 14

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users and roles

simple rights management via user accounts and connection to external directory services

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.