DBMS > Alibaba Cloud MaxCompute vs. Cubrid vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. PouchDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Cubrid vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. PouchDB

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

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

Widely used in-process key-value store

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

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

Relational DBMS

Key-value store
Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.alibabacloud.com/product/maxcompute

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

cloud.google.com/bigtable

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

pouchdb.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cubrid.org/manuals

cloud.google.com/bigtable/docs

docs.oracle.com/cd/E17076_05/html/index.html

pouchdb.com/guides

Developer

Alibaba

CUBRID Corporation, CUBRID Foundation

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation

Initial release

2016

2008

2015

1994

2012

Current release

11.0, January 2021

18.1.40, May 2020

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

commercial license available

Open Source

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

C, Java, C++ (depending on the Berkeley DB edition)

JavaScript

Server operating systems

hosted

Linux
Windows

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
ODBC
OLE DB

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java

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

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Java

Java Stored Procedures

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

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

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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)

Eventual Consistency

Foreign keys

Referential integrity

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

by using IndexedDB, WebSQL or LevelDB as backend

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)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the news

Streaming Data Services Comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM Cloud
20 January 2020, Wire19

Denodo and Alibaba Cloud Join Forces to Deliver Logical Data Integration and Management
5 July 2023, AiThority

How Big Data Platform Helped Power Last Year's Double 11
3 March 2020, DataDrivenInvestor

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

Alibaba VP Yangqing Jia to Quit and Start Own AI Business
21 March 2023, Pandaily

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

EC will investigate the Oracle/Sun takeover due to concerns about MySQL
3 September 2009, The Guardian

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

A Quick Look at Open Source Databases for Mobile App Development
29 April 2018, Open Source For You

Motorola A780 Linux based smartphone to have mobile database
14 September 2004, Geekzone

provided by Google News

Building an Offline First App with PouchDB — SitePoint
10 March 2014, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database — SitePoint
7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
7 March 2017, SitePoint

Offline-first web and mobile apps: Top frameworks and components
22 January 2019, TechBeacon

provided by Google News

Share this page