DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Kinetica vs. NCache vs. SAP HANA

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Kinetica vs. NCache 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

Large scale data warehouse service for use with business intelligence tools

Fully vectorized database across both GPUs and CPUs

Open-Source and Enterprise in-memory Key-Value Store

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

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Search engine

Using distributed Lucene

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	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

www.kinetica.com

www.alachisoft.com/ncache

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

docs.kinetica.com

www.alachisoft.com/resources/docs

help.sap.com/hana

Developer

Alibaba

Amazon (based on PostgreSQL)

Kinetica

Alachisoft

SAP

Initial release

2016

2012

2005

2010

Current release

7.1, August 2021

5.3.3, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

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

C, C++

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux

Linux
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC

C++
Java
JavaScript (Node.js)
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

user defined functions

support for stored procedures with SQL-Server CLR

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

yes

More information provided by the system vendor

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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