DBMS > Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Kinetica vs. Oracle vs. PlanetScale

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Kinetica vs. Oracle vs. PlanetScale

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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Fully vectorized database across both GPUs and CPUs

Widely used RDBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Relational DBMS

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

Document store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/documentdb

www.kinetica.com

www.oracle.com/database

planetscale.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

aws.amazon.com/documentdb/resources

docs.kinetica.com

docs.oracle.com/en/database

planetscale.com/docs

Developer

Alibaba

Kinetica

Oracle

PlanetScale

Initial release

2016

2019

2012

1980

2020

Current release

7.1, August 2021

23c, September 2023

License

Commercial or Open Source

commercial

restricted free version is 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

C, C++

C and C++

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
PHP
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

PL/SQL

also stored procedures in Java possible

yes

proprietary syntax

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-document operations

ACID

isolation level can be parameterized

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

GPU vRAM or System RAM

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users and roles

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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