DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. Graph Engine vs. Oracle NoSQL vs. OrigoDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Bigtable vs. Graph Engine vs. Oracle NoSQL vs. OrigoDB

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

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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

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

Key-value store
Wide column store

Graph DBMS
Key-value store

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

www.alibabacloud.com/product/maxcompute

cloud.google.com/bigtable

www.graphengine.io

www.oracle.com/database/nosql/technologies/nosql

origodb.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

docs.oracle.com/en/database/other-databases/nosql-database/index.html

origodb.com/docs

Developer

Alibaba

Google

Microsoft

Oracle

Robert Friberg et al

Initial release

2016

2015

2010

2011

2009

under the name LiveDB

Current release

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

.NET and C

Java

Server operating systems

hosted

.NET

Linux
Solaris SPARC/x86

Linux
Windows

Data scheme

yes

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Supported programming languages

Java

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

C#
C++
F#
Visual Basic

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

.Net

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Sharding

horizontal partitioning

client side managed; servers are not synchronized

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

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

depending on configuration

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Atomic single-row operations

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

Access rights for users and roles

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

Access rights for users and roles

Role based authorization

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