DBMS > Badger vs. dBASE vs. Google BigQuery vs. Hawkular Metrics

System Properties Comparison Badger vs. dBASE vs. Google BigQuery vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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Trend Chart

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Website

github.com/dgraph-io/badger

www.dbase.com

cloud.google.com/bigquery

www.hawkular.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

DGraph Labs

Asthon Tate

Google

Community supported by Red Hat

Initial release

2017

1979

2010

2014

Current release

dBASE 2019, 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

BSD
Linux
OS X
Solaris
Windows

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

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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