DBMS > Alibaba Cloud MaxCompute vs. Blazegraph vs. Datomic vs. Graph Engine vs. RDF4J

System Properties Comparison Alibaba Cloud MaxCompute vs. Blazegraph vs. Datomic vs. Graph Engine vs. RDF4J

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

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

Graph DBMS
RDF store

Relational DBMS

Graph DBMS
Key-value store

RDF store

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

www.alibabacloud.com/product/maxcompute

Technical documentation

www.alibabacloud.com/help/en/maxcompute

wiki.blazegraph.com

docs.datomic.com

www.graphengine.io/docs/manual

rdf4j.org/documentation

Developer

Alibaba

Blazegraph

Cognitect

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2006

2012

2010

2004

Current release

2.1.5, March 2019

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

commercial

limited edition free

Open Source

MIT License

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java, Clojure

.NET and C

Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

.NET

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

RDF literal types

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SPARQL is used as query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Clojure
Java

C#
C++
F#
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

But extensive use of caching in the application peers

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

But extensive use of caching in the application peers

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

Security and Authentication via Web Application Container (Tomcat, Jetty)

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