DBMS > Alibaba Cloud MaxCompute vs. Hive vs. ITTIA vs. Microsoft Azure Cosmos DB vs. SAP HANA

System Properties Comparison Alibaba Cloud MaxCompute vs. Hive vs. ITTIA vs. Microsoft Azure Cosmos DB 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

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

Edge Time Series DBMS with Real-Time Stream Processing

Globally distributed, horizontally scalable, multi-model database service

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

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Relational DBMS

Spatial 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	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

hive.apache.org

www.ittia.com

azure.microsoft.com/services/cosmos-db

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

learn.microsoft.com/azure/cosmos-db

help.sap.com/hana

Developer

Alibaba

Apache Software Foundation

initially developed by Facebook

ITTIA L.L.C.

Microsoft

SAP

Initial release

2016

2012

2007

2014

2010

Current release

3.1.3, April 2022

8.7

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

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

C and C++

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

hosted

Appliance or cloud-service

Data scheme

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

JSON types

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

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
Thrift

JDBC
ODBC
RESTful HTTP API
WebSocket

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

Supported programming languages

Java

C++
Java
PHP
Python

C
C++
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

yes

JavaScript

SQLScript, R

Triggers

JavaScript

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

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

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users, groups and roles

Database file passwords

Access rights can be defined down to the item level

yes

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