DBMS > Alibaba Cloud MaxCompute vs. DataFS vs. KairosDB vs. Titan vs. Yanza

System Properties Comparison Alibaba Cloud MaxCompute vs. DataFS vs. KairosDB vs. Titan vs. Yanza

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Yanza seems to be discontinued. Therefore it 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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Distributed Time Series DBMS based on Cassandra or H2

Titan is a Graph DBMS optimized for distributed clusters.

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

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

Secondary database models

Graph DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

newdatabase.com

github.com/kairosdb/kairosdb

github.com/thinkaurelius/titan

yanza.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

dev.mobiland.com/Overview.xsp

kairosdb.github.io

github.com/thinkaurelius/titan/wiki

Developer

Alibaba

Mobiland AG

Aurelius, owned by DataStax

Yanza

Initial release

2016

2018

2013

2012

2015

Current release

1.1.263, October 2022

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache license, version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

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

Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

.NET Client API
Proprietary client DLL
WinRT client

Graphite protocol
HTTP REST
Telnet API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API

Supported programming languages

Java

.Net
C
C#
C++
VB.Net

Java
JavaScript

Node.js
PHP
Python

Clojure
Java
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Triggers

no, except callback-events from server when changes happened

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Proprietary Sharding system

Sharding

based on Cassandra

yes

via pluggable storage backends

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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

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.

User concepts

Access control

Access rights for users and roles

Windows-Profile

simple password-based access control

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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