DBMS > Alibaba Cloud MaxCompute vs. Google Cloud Spanner vs. Hive vs. Hypertable vs. SAP HANA

System Properties Comparison Alibaba Cloud MaxCompute vs. Google Cloud Spanner vs. Hive vs. Hypertable vs. SAP HANA

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

In-memory, column based data store. Available as appliance or cloud service

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

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

cloud.google.com/spanner

hive.apache.org

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cloud.google.com/spanner/docs

cwiki.apache.org/confluence/display/Hive/Home

help.sap.com/hana

Developer

Alibaba

Google

Apache Software Foundation

initially developed by Facebook

Hypertable Inc.

SAP

Initial release

2016

2017

2012

2009

2010

Current release

3.1.3, April 2022

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

yes

Query statements complying to ANSI 2011

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Thrift

C++ API
Thrift

JDBC
ODBC

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
Python

C++
Java
PHP
Python

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles

yes

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