DBMS > Alibaba Cloud MaxCompute vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. OpenTSDB vs. Stardog

System Properties Comparison Alibaba Cloud MaxCompute vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. OpenTSDB 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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

Scalable Time Series DBMS based on HBase

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

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.alibabacloud.com/product/maxcompute

janusgraph.org

azure.microsoft.com/services/cosmos-db

opentsdb.net

www.stardog.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

opentsdb.net/docs/build/html/index.html

docs.stardog.com

Developer

Alibaba

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

currently maintained by Yahoo and other contributors

Stardog-Union

Initial release

2016

2017

2014

2011

2010

Current release

0.6.3, February 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

LGPL

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

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Unix
Windows

hosted

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

JSON types

numeric data for metrics, strings for tags

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

All properties auto-indexed by default

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

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

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API
Telnet API

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

Clojure
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Erlang
Go
Java
Python
R
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

yes

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

JavaScript

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

based on HBase

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

Access rights for users and roles

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