DBMS > Alibaba Cloud MaxCompute vs. JanusGraph vs. LevelDB vs. Microsoft Azure Cosmos DB vs. MonetDB

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

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Primary database model

Relational DBMS

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

Graph DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
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	2.25
Rank	#115	Overall
	#19	Key-value stores

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

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

janusgraph.org

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

www.monetdb.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.janusgraph.org

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

Developer

Alibaba

Linux Foundation; originally developed as Titan by Aurelius

Google

Microsoft

MonetDB BV

Initial release

2016

2017

2011

2014

2004

Current release

0.6.3, February 2023

1.23, February 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

commercial

Open Source

Mozilla Public License 2.0

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

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Illumos
Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

Java

Clojure
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

yes

JavaScript

yes, in SQL, C, R

Triggers

yes

JavaScript

yes

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)

none

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

with automatic compression on writes

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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