DBMS > Alibaba Cloud MaxCompute vs. Apache Impala vs. Coveo vs. Drizzle vs. Microsoft SQL Server

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Impala vs. Coveo vs. Drizzle vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

Analytic DBMS for Hadoop

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

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

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

impala.apache.org

www.coveo.com

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

Technical documentation

www.alibabacloud.com/help/en/maxcompute

impala.apache.org/impala-docs.html

docs.coveo.com

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

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Coveo

Drizzle project, originally started by Brian Aker

Microsoft

Initial release

2016

2013

2012

2008

1989

Current release

4.1.0, June 2022

7.2.4, September 2012

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

GNU GPL

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
OS X

Linux
Windows

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

RESTful HTTP API

JDBC

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

Supported programming languages

Java

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

C
C++
Java
PHP

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

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

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

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

yes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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 Apache Sentry and Kerberos

granular access controls, API key management, content filters

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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