DBMS > Alibaba Cloud MaxCompute vs. Amazon DynamoDB vs. Apache Druid vs. Microsoft Azure Data Explorer

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DynamoDB vs. Apache Druid vs. Microsoft Azure Data Explorer

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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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Fully managed big data interactive analytics platform

Primary database model

Relational DBMS

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

Document store
Key-value store

Relational DBMS
Time Series DBMS

Relational DBMS

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/dynamodb

druid.apache.org

azure.microsoft.com/services/data-explorer

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

docs.microsoft.com/en-us/azure/data-explorer

Developer

Alibaba

Amazon

Apache Software Foundation and contributors

Microsoft

Initial release

2016

2012

2019

Current release

29.0.1, April 2024

cloud service with continuous releases

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

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

Java

Server operating systems

hosted

Linux
OS X
Unix

hosted

Data scheme

yes

schema-free

yes

schema-less columns are supported

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL for querying

Kusto Query Language (KQL), SQL subset

APIs and other access methods

Fluentd
Flume
MaxCompute Console

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

Java

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

user defined functions

in Java

Yes, possible languages: KQL, Python, R

Triggers

yes

by integration with AWS Lambda

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

manual/auto, time-based

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

yes, via HDFS, S3 or other storage engines

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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 and roles can be defined via the AWS Identity and Access Management (IAM)

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Azure Active Directory Authentication

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