DBMS > Alibaba Cloud PolarDB vs. BigchainDB vs. dBASE vs. Google BigQuery vs. Kinetica

System Properties Comparison Alibaba Cloud PolarDB vs. BigchainDB vs. dBASE vs. Google BigQuery vs. Kinetica

Editorial information provided by DB-Engines

Name

Description

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

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

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

Fully vectorized database across both GPUs and CPUs

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.59
Rank	#241	Overall
	#110	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

www.alibabacloud.com/product/polardb

www.bigchaindb.com

www.dbase.com

cloud.google.com/bigquery

www.kinetica.com

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

bigchaindb.readthedocs.io/en/latest

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

docs.kinetica.com

Developer

Alibaba

Asthon Tate

Google

Kinetica

Initial release

2016

1979

2010

2012

Current release

dBASE 2019, 2019

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

AGPL v3

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

C, C++

Server operating systems

hosted

Linux

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

More information provided by the system vendor

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Typical application scenarios

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Licensing and pricing models

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