DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Apache Impala vs. dBASE vs. Google BigQuery

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Apache Impala vs. dBASE vs. Google BigQuery

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Analytic DBMS for Hadoop

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

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Relational DBMS

Secondary database models

Document store

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.alibabacloud.com/product/maxcompute

impala.apache.org

www.dbase.com

cloud.google.com/bigquery

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.alibabacloud.com/help/en/maxcompute

impala.apache.org/impala-docs.html

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Asthon Tate

Google

Initial release

2016

2013

1979

2010

Current release

4.1.0, June 2022

dBASE 2019, 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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

C++

Server operating systems

hosted

Linux

DOS

dBase Classic
Windows

dBase Pro

hosted

Data scheme

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 query language

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

Java

All languages supporting JDBC/ODBC

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in Java

yes

user defined functions and integration of map-reduce

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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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