DBMS > Alibaba Cloud MaxCompute vs. Google BigQuery vs. Graph Engine vs. Microsoft Access vs. Rockset

System Properties Comparison Alibaba Cloud MaxCompute vs. Google BigQuery vs. Graph Engine vs. Microsoft Access vs. Rockset

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

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

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	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

www.alibabacloud.com/product/maxcompute

cloud.google.com/bigquery

www.graphengine.io

www.microsoft.com/en-us/microsoft-365/access

rockset.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

developer.microsoft.com/en-us/access

docs.rockset.com

Developer

Alibaba

Google

Microsoft

Rockset

Initial release

2016

2010

1992

2019

Current release

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Bundled with Microsoft Office

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

.NET and C

C++

Server operating systems

hosted

.NET

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

but not compliant to any SQL standard

Read-only SQL queries, including JOINs

APIs and other access methods

Fluentd
Flume
MaxCompute Console

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

HTTP REST

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

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

but no files for transaction logging

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

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

Google Cloud Identity & Access Management (IAM)

a simple user-level security was built in till version Access 2003

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

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.