DBMS > Apache Drill vs. Axibase vs. dBASE vs. Dolt vs. Google BigQuery

System Properties Comparison Apache Drill vs. Axibase vs. dBASE vs. Dolt vs. Google BigQuery

Editorial information provided by DB-Engines

Name

Description

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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.

A MySQL compatible DBMS with Git-like versioning of data and schema

Large scale data warehouse service with append-only tables

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

drill.apache.org

axibase.com/docs/atsd/finance

www.dbase.com

github.com/dolthub/dolt
www.dolthub.com

cloud.google.com/bigquery

Technical documentation

drill.apache.org/docs

www.dbase.com/support/knowledgebase

docs.dolthub.com

cloud.google.com/bigquery/docs

Developer

Apache Software Foundation

Axibase Corporation

Asthon Tate

DoltHub Inc

Google

Initial release

2012

2013

1979

2018

2010

Current release

1.20.3, January 2023

15585

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache Version 2.0

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

Java

Server operating systems

Linux
OS X
Windows

Linux

DOS

dBase Classic
Windows

dBase Pro

Linux
macOS
Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

CLI Client
HTTP REST

RESTful HTTP/JSON API

Supported programming languages

C++

Go
Java
PHP
Python
R
Ruby

dBase proprietary IDE

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

The IDE can access stored procedures in other database systems.

yes

currently in alpha release

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

Depending on the underlying data source

Access rights for users and roles

Only one user is configurable, and must be specified in the config file at startup

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

Google Cloud Identity & Access Management (IAM)

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