DBMS > Alibaba Cloud MaxCompute vs. Citus vs. Hive vs. Microsoft Azure AI Search vs. SAP HANA

System Properties Comparison Alibaba Cloud MaxCompute vs. Citus vs. Hive vs. Microsoft Azure AI Search vs. SAP HANA

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Search-as-a-service for web and mobile app development

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

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

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store

Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.citusdata.com

hive.apache.org

azure.microsoft.com/en-us/services/search

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.citusdata.com

cwiki.apache.org/confluence/display/Hive/Home

learn.microsoft.com/en-us/azure/search

help.sap.com/hana

Developer

Alibaba

Apache Software Foundation

initially developed by Facebook

Microsoft

SAP

Initial release

2016

2010

2012

2015

2010

Current release

8.1, December 2018

3.1.3, April 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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

All OS with a Java VM

hosted

Appliance or cloud-service

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

SQL

Support of SQL

SQL-like query language

yes

standard, with numerous extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

JDBC
ODBC
Thrift

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

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

yes

user defined functions and integration of map-reduce

SQLScript, R

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes

Implicit feature of the cloud service

yes

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

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.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

yes

using Azure authentication

yes

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