DBMS > Alibaba Cloud MaxCompute vs. GridDB vs. Microsoft Azure Cosmos DB vs. SAP IQ

System Properties Comparison Alibaba Cloud MaxCompute vs. GridDB vs. Microsoft Azure Cosmos DB vs. SAP IQ

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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

Scalable in-memory time series database optimized for IoT and Big Data

Globally distributed, horizontally scalable, multi-model database service

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

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

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

column-oriented

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

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

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

griddb.net

azure.microsoft.com/services/cosmos-db

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.griddb.net

learn.microsoft.com/azure/cosmos-db

help.sap.com/docs/SAP_IQ

Developer

Alibaba

Toshiba Corporation

Microsoft

SAP, formerly Sybase

Initial release

2016

2013

2014

1994

Current release

5.1, August 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

JavaScript

yes

Triggers

yes

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

Implicit feature of the cloud service

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

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

ACID at container level

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights for users can be defined per database

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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