DBMS > Alibaba Cloud MaxCompute vs. Apache Impala vs. SiteWhere vs. Snowflake

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Impala vs. SiteWhere vs. Snowflake

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Name

Description

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

Analytic DBMS for Hadoop

M2M integration platform for persisting/querying time series data

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

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

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

impala.apache.org

github.com/sitewhere/sitewhere

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

impala.apache.org/impala-docs.html

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

SiteWhere

Snowflake Computing Inc.

Initial release

2016

2013

2010

2014

Current release

4.1.0, June 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Common Public Attribution License Version 1.0

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++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

hosted

Data scheme

yes

predefined scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

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.

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept

Users with fine-grained authorization concept, user roles and pluggable authentication

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