DBMS > BigchainDB vs. Datomic vs. dBASE vs. Google BigQuery

System Properties Comparison BigchainDB vs. Datomic vs. dBASE vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

Large scale data warehouse service with append-only tables

Primary database model

Document store

Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

www.bigchaindb.com

www.datomic.com

www.dbase.com

cloud.google.com/bigquery

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.datomic.com

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

Developer

Cognitect

Asthon Tate

Google

Initial release

2016

2012

1979

2010

Current release

1.0.6735, June 2023

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

AGPL v3

commercial

limited edition free

commercial

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

Python

Java, Clojure

Server operating systems

Linux

All OS with a Java VM

DOS

dBase Classic
Windows

dBase Pro

hosted

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

User concepts

Access control

yes

Access rights for users and roles

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

Google Cloud Identity & Access Management (IAM)

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