DBMS > dBASE vs. FileMaker vs. Google BigQuery vs. Hazelcast vs. Splice Machine

System Properties Comparison dBASE vs. FileMaker vs. Google BigQuery vs. Hazelcast vs. Splice Machine

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.

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

Large scale data warehouse service with append-only tables

A widely adopted in-memory data grid

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.dbase.com

www.claris.com/filemaker

cloud.google.com/bigquery

hazelcast.com

splicemachine.com

Technical documentation

www.dbase.com/support/knowledgebase

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

hazelcast.org/imdg/docs

splicemachine.com/how-it-works

Developer

Asthon Tate

Claris

a subsidiary of Apple

Google

Hazelcast

Splice Machine

Initial release

1979

1983

2010

2008

2014

Current release

dBASE 2019, 2019

19.4.1, November 2021

5.3.6, November 2023

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

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

DOS

dBase Classic
Windows

dBase Pro

iOS

client part only
Linux
OS X
Windows

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

yes

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

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

SQL-like query language

yes

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

dBase proprietary IDE

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

user defined functions

in JavaScript

yes

Event Listeners, Executor Services

yes

Java

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes

Replicated Map

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

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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)

Role-based access control

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

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