DBMS > Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. SAP HANA vs. Spark SQL vs. Stardog

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. SAP HANA vs. Spark SQL vs. Stardog

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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

In-memory, column based data store. Available as appliance or cloud service

Spark SQL is a component on top of 'Spark Core' for structured data processing

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

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

Document store

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/documentdb

www.sap.com/products/hana.html

spark.apache.org/sql

www.stardog.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

aws.amazon.com/documentdb/resources

help.sap.com/hana

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

Developer

Alibaba

SAP

Apache Software Foundation

Stardog-Union

Initial release

2016

2019

2010

2014

2010

Current release

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Java

Server operating systems

hosted

Appliance or cloud-service

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Fluentd
Flume
MaxCompute Console

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
PHP
Python

Java
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

SQLScript, R

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

relationships in graphs

Transaction concepts

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

Atomic single-document operations

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

Access rights for users and roles

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