DBMS > Alibaba Cloud MaxCompute vs. Cubrid vs. Google Cloud Datastore vs. TimesTen

System Properties Comparison Alibaba Cloud MaxCompute vs. Cubrid vs. Google Cloud Datastore vs. TimesTen

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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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

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

Relational DBMS

Document store

Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

cubrid.com (korean)
cubrid.org (english)

cloud.google.com/datastore

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cubrid.org/manuals

cloud.google.com/datastore/docs

docs.oracle.com/database/timesten-18.1

Developer

Alibaba

CUBRID Corporation, CUBRID Foundation

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2008

1998

Current release

11.0, January 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 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

C, C++, Java

Server operating systems

hosted

Linux
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

yes

SQL-like query language (GQL)

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

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

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Java

Java Stored Procedures

using Google App Engine

PL/SQL

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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