DBMS > Alibaba Cloud MaxCompute vs. Alibaba Cloud TSDB vs. Apache IoTDB vs. Microsoft SQL Server vs. Tigris

System Properties Comparison Alibaba Cloud MaxCompute vs. Alibaba Cloud TSDB vs. Apache IoTDB vs. Microsoft SQL Server vs. Tigris

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

A stable, reliable, and cost-effective online high-performance time series database service

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

Microsofts flagship relational DBMS

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

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

Time Series DBMS

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.29
Rank	#301	Overall
	#26	Time Series DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

www.alibabacloud.com/product/hitsdb

iotdb.apache.org

www.microsoft.com/en-us/sql-server

www.tigrisdata.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

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

learn.microsoft.com/en-US/sql/sql-server

www.tigrisdata.com/docs

Developer

Alibaba

Apache Software Foundation

Microsoft

Tigris Data, Inc.

Initial release

2016

2018

1989

2022

Current release

1.1.0, April 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

HTTP REST

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Java

C
C#
C++
Go
Java
Python
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

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)

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

yes, but depending on the SQL-Server Edition

yes

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

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

yes, using FoundationDB

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

Access managed on TSDB instance level

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

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