DBMS > Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. Google BigQuery vs. Graph Engine vs. Rockset

System Properties Comparison Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. Google BigQuery vs. Graph Engine vs. Rockset

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Large scale data warehouse service with append-only tables

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

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

Document store
Key-value store

Relational DBMS

Graph DBMS
Key-value store

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

www.alibabacloud.com/product/maxcompute

atos.net/en/convergence-creators/portfolio/standard-common-repository

cloud.google.com/bigquery

www.graphengine.io

rockset.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

docs.rockset.com

Developer

Alibaba

Atos Convergence Creators

Google

Microsoft

Rockset

Initial release

2016

2010

2019

Current release

1703

License

Commercial or Open Source

commercial

Open Source

MIT License

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

.NET and C

C++

Server operating systems

hosted

Linux

hosted

.NET

hosted

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

Fluentd
Flume
MaxCompute Console

LDAP

RESTful HTTP/JSON API

RESTful HTTP API

HTTP REST

Supported programming languages

Java

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

cell division

none

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Since BigQuery is designed for querying data

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

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

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and organizations can be defined via Rockset console

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