DBMS > DataFS vs. Google Cloud Bigtable vs. HugeGraph vs. MonetDB vs. PieCloudDB

System Properties Comparison DataFS vs. Google Cloud Bigtable vs. HugeGraph vs. MonetDB vs. PieCloudDB

Editorial information provided by DB-Engines

Name

Description

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A fast-speed and highly-scalable Graph DBMS

A relational database management system that stores data in columns

A cloud-native analytic database platform with new technologoy for elastic MPP

Primary database model

Object oriented DBMS

Key-value store
Wide column store

Graph DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Website

newdatabase.com

cloud.google.com/bigtable

github.com/hugegraph
hugegraph.apache.org

www.monetdb.org

www.openpie.com

Technical documentation

dev.mobiland.com/Overview.xsp

cloud.google.com/bigtable/docs

hugegraph.apache.org/docs

www.monetdb.org/Documentation

Developer

Mobiland AG

Google

Baidu

MonetDB BV

OpenPie

Initial release

2018

2015

2018

2004

Current release

1.1.263, October 2022

0.9

Dec2023 (11.49), December 2023

2.1, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

commercial

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

Windows

hosted

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

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

schema-free

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
C++
Go
Java
JavaScript (Node.js)
Python

Groovy
Java
Python

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

Java
PL/SQL
Python
R

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, in SQL, C, R

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Atomic single-row 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

Windows-Profile

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users, roles and permissions

fine grained access rights according to SQL-standard

User Roles and pluggable authentication with full SQL Standard

More information provided by the system vendor

Specific characteristics

PieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more

Competitive advantages

Extreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more

Typical application scenarios

PieCloudDB is ideal for Data mining applications that require extreme scalability...
» more

Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
» more

Licensing and pricing models

PieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment；...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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