DBMS > Alibaba Cloud MaxCompute vs. Blazegraph vs. H2 vs. Pinecone vs. PostgreSQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Blazegraph vs. H2 vs. Pinecone vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A managed, cloud-native vector database

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Relational DBMS

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

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

Technical documentation

www.alibabacloud.com/help/en/maxcompute

wiki.blazegraph.com

www.h2database.com/html/main.html

docs.pinecone.io/docs/overview

www.postgresql.org/docs

Developer

Alibaba

Blazegraph

Thomas Mueller

Pinecone Systems, Inc

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2016

2006

2005

2019

1989

1989: Postgres, 1996: PostgreSQL

Current release

2.1.5, March 2019

2.2.220, July 2023

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

String, Number, Boolean

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SPARQL is used as query language

yes

standard with numerous extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java

Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Java Stored Procedures and User-Defined Functions

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

other methods possible by using 3rd party extensions

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

Relationships in Graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

fine grained access rights according to SQL-standard

More information provided by the system vendor

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