DBMS > Alibaba Cloud MaxCompute vs. Apache Kylin vs. Google Cloud Firestore vs. Microsoft SQL Server vs. TerarkDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Kylin vs. Google Cloud Firestore vs. Microsoft SQL Server vs. TerarkDB

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 distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.alibabacloud.com/product/maxcompute

kylin.apache.org

firebase.google.com/products/firestore

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

github.com/bytedance/terarkdb

Technical documentation

www.alibabacloud.com/help/en/maxcompute

kylin.apache.org/docs

firebase.google.com/docs/firestore

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Alibaba

Apache Software Foundation, originally contributed from eBay Inc

Google

Microsoft

ByteDance, originally Terark

Initial release

2016

2015

2017

1989

2016

Current release

3.1.0, July 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

hosted

Linux

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

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

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

C++ API
Java API

Supported programming languages

Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Java

yes, Firebase Rules & Cloud Functions

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

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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