DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. HarperDB vs. SQLite

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Atos Standard Common Repository vs. HarperDB vs. SQLite

Editorial information provided by DB-Engines

Name

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

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

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

Document store
Key-value store

Document store

Relational DBMS

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.alibabacloud.com/product/maxcompute

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

www.harperdb.io

www.sqlite.org

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.alibabacloud.com/help/en/maxcompute

docs.harperdb.io/docs

www.sqlite.org/docs.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Alibaba

Atos Convergence Creators

HarperDB

Dwayne Richard Hipp

Initial release

2016

2017

2000

Current release

1703

3.1, August 2021

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Public Domain

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

Node.js

Server operating systems

hosted

Linux

Linux
OS X

server-less

Data scheme

yes

Schema and schema-less with LDAP views

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

yes

JSON data types

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-like query language

SQL-like data manipulation statements

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

Fluentd
Flume
MaxCompute Console

LDAP

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
Java
Perl
Python
R

Java

All languages with LDAP bindings

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

in Java

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

cell division

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

yes

the nodes on which a table resides can be defined

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, using LMDB

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

fine grained access rights according to SQL-standard

Access rights for users and roles

LDAP bind authentication

Access rights for users and roles

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