DBMS > Amazon Redshift vs. Apache Drill vs. Blueflood vs. dBASE vs. Google Cloud Bigtable

System Properties Comparison Amazon Redshift vs. Apache Drill vs. Blueflood vs. dBASE vs. Google Cloud Bigtable

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Scalable TimeSeries DBMS based on Cassandra

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Primary database model

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store
Wide column store

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Website

aws.amazon.com/redshift

drill.apache.org

blueflood.io

www.dbase.com

cloud.google.com/bigtable

Technical documentation

docs.aws.amazon.com/redshift

drill.apache.org/docs

github.com/rax-maas/blueflood/wiki

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Rackspace

Asthon Tate

Google

Initial release

2012

2013

1979

2015

Current release

1.20.3, January 2023

dBASE 2019, 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 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

hosted

Linux
OS X
Windows

Linux
OS X

DOS

dBase Classic
Windows

dBase Pro

hosted

Data scheme

yes

schema-free

predefined scheme

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

HTTP REST

none

The IDE can access other DBMS or ODBC-sources.

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

All languages supporting JDBC/ODBC

C++

dBase proprietary IDE

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

The IDE can access stored procedures in other database systems.

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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.

yes

Depending on the underlying data source

User concepts

Access control

fine grained access rights according to SQL-standard

Depending on the underlying data source

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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