DBMS > Alibaba Cloud MaxCompute vs. Datomic vs. Google BigQuery vs. Hypertable vs. SAP SQL Anywhere

System Properties Comparison Alibaba Cloud MaxCompute vs. Datomic vs. Google BigQuery vs. Hypertable vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is 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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Large scale data warehouse service with append-only tables

An open source BigTable implementation based on distributed file systems such as Hadoop

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

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

Relational DBMS

Wide column 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.datomic.com

cloud.google.com/bigquery

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.datomic.com

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Alibaba

Cognitect

Google

Hypertable Inc.

SAP

formerly Sybase

Initial release

2016

2012

2010

2009

1992

Current release

1.0.6735, June 2023

0.9.8.11, March 2016

17, July 2015

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

GNU version 3. Commercial license available

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, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

RESTful HTTP API

RESTful HTTP/JSON API

C++ API
Thrift

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Transaction Functions

user defined functions

in JavaScript

yes, in C/C++, Java, .Net or Perl

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

selectable replication factor on file system level

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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)

fine grained access rights according to SQL-standard

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