DBMS > Alibaba Cloud MaxCompute vs. Amazon CloudSearch vs. Google BigQuery vs. PostgreSQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon CloudSearch vs. Google BigQuery vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

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

A hosted search engine service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service with append-only tables

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Relational DBMS

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

Search engine

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/cloudsearch

cloud.google.com/bigquery

www.postgresql.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/cloudsearch

cloud.google.com/bigquery/docs

www.postgresql.org/docs

Developer

Alibaba

Amazon

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2016

2012

2010

1989

1989: Postgres, 1996: PostgreSQL

Current release

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Server operating systems

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in JavaScript

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

automatic partitioning across Amazon Search Instance as required

none

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

managed transparently by AWS

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

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

authentication via encrypted signatures

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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