DBMS > Alibaba Cloud MaxCompute vs. AnzoGraph DB vs. Apache Druid vs. Microsoft SQL Server

System Properties Comparison Alibaba Cloud MaxCompute vs. AnzoGraph DB vs. Apache Druid vs. Microsoft SQL Server

Please select another system to include it in the comparison.

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

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

Graph DBMS
RDF store

Relational DBMS
Time Series DBMS

Relational DBMS

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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

cambridgesemantics.com/anzograph

druid.apache.org

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

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

druid.apache.org/docs/latest/design

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

Developer

Alibaba

Cambridge Semantics

Apache Software Foundation and contributors

Microsoft

Initial release

2016

2018

2012

1989

Current release

2.3, January 2021

29.0.1, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache license v2

commercial

restricted free version is available

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++

Server operating systems

hosted

Linux

Linux
OS X
Unix

Linux
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

schema-less columns are supported

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

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL for querying

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
RESTful HTTP/JSON API

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

Supported programming languages

Java

C++
Java
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions and aggregates

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

Automatic sharding

Sharding

manual/auto, time-based

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

Multi-source replication in MPP-Cluster

yes, via HDFS, S3 or other storage engines

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.