DBMS > 4D vs. Alibaba Cloud MaxCompute vs. KairosDB vs. Microsoft Azure Data Explorer

System Properties Comparison 4D vs. Alibaba Cloud MaxCompute vs. KairosDB vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Distributed Time Series DBMS based on Cassandra or H2

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

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Website

www.4d.com

www.alibabacloud.com/product/maxcompute

github.com/kairosdb/kairosdb

azure.microsoft.com/services/data-explorer

Technical documentation

developer.4d.com

www.alibabacloud.com/help/en/maxcompute

kairosdb.github.io

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

Developer

4D, Inc

Alibaba

Microsoft

Initial release

1984

2016

2013

2019

Current release

v20, April 2023

1.2.2, November 2018

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

OS X
Windows

hosted

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

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

yes

close to SQL 92

SQL-like query language

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Fluentd
Flume
MaxCompute Console

Graphite protocol
HTTP REST
Telnet API

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

Supported programming languages

4D proprietary IDE
PHP

Java

Java
JavaScript

Node.js
PHP
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

in Java

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

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

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Users and groups

Access rights for users and roles

simple password-based access control

Azure Active Directory Authentication

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More resources

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