DBMS > Alibaba Cloud MaxCompute vs. DataFS vs. Google Cloud Bigtable vs. HarperDB vs. RDF4J

System Properties Comparison Alibaba Cloud MaxCompute vs. DataFS vs. Google Cloud Bigtable vs. HarperDB vs. RDF4J

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

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Object oriented DBMS

Key-value store
Wide column store

Document store

RDF store

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.alibabacloud.com/product/maxcompute

newdatabase.com

cloud.google.com/bigtable

www.harperdb.io

rdf4j.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

dev.mobiland.com/Overview.xsp

cloud.google.com/bigtable/docs

docs.harperdb.io/docs

rdf4j.org/documentation

Developer

Alibaba

Mobiland AG

Google

HarperDB

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

Initial release

2016

2018

2015

2017

2004

Current release

1.1.263, October 2022

3.1, August 2021

License

Commercial or Open Source

commercial

free community edition available

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

Node.js

Java

Server operating systems

hosted

Windows

hosted

Linux
OS X

Linux
OS X
Unix
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

dynamic schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

JSON data 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

SQL-like data manipulation statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

.NET Client API
Proprietary client DLL
WinRT client

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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#
C++
VB.Net

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Java

Custom Functions

since release 3.1

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Proprietary Sharding system

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

yes

the nodes on which a table resides can be defined

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

Atomic execution of specific operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

User concepts

Access control

Access rights for users and roles

Windows-Profile

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

Access rights for users and roles

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