DBMS > Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Brytlyt vs. KairosDB vs. Microsoft Azure SQL Database

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Brytlyt vs. KairosDB vs. Microsoft Azure SQL Database

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Distributed Time Series DBMS based on Cassandra or H2

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Relational DBMS

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

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

iotdb.apache.org

brytlyt.io

github.com/kairosdb/kairosdb

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

www.alibabacloud.com/help/en/maxcompute

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.brytlyt.io

kairosdb.github.io

docs.microsoft.com/en-us/azure/azure-sql

Developer

Alibaba

Apache Software Foundation

Brytlyt

Microsoft

Initial release

2016

2018

2016

2013

2010

Current release

1.1.0, April 2023

5.0, August 2023

1.2.2, November 2018

V12

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

C, C++ and CUDA

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

yes

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
Native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java
JavaScript

Node.js
PHP
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions

in PL/pgSQL

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

selectable replication factor

based on Cassandra

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

yes

User concepts

Access control

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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