DBMS > BoltDB vs. Datomic vs. dBASE vs. Google Cloud Firestore vs. SQLite

System Properties Comparison BoltDB vs. Datomic vs. dBASE vs. Google Cloud Firestore vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/boltdb/bolt

www.datomic.com

www.dbase.com

firebase.google.com/products/firestore

www.sqlite.org

Technical documentation

docs.datomic.com

www.dbase.com/support/knowledgebase

firebase.google.com/docs/firestore

www.sqlite.org/docs.html

Developer

Cognitect

Asthon Tate

Google

Dwayne Richard Hipp

Initial release

2013

2012

1979

2017

2000

Current release

1.0.7075, December 2023

dBASE 2019, 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

limited edition free

commercial

Open Source

Public Domain

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, Clojure

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

DOS

dBase Classic
Windows

dBase Pro

hosted

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
Java

dBase proprietary IDE

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

The IDE can access stored procedures in other database systems.

yes, Firebase Rules & Cloud Functions

Triggers

By using transaction functions

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

yes

ACID

not for dBase internal data, but IDE does support transactions when accessing external DBMS

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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