DBMS > Alibaba Cloud MaxCompute vs. Heroic vs. Linter vs. mSQL vs. Pinecone

System Properties Comparison Alibaba Cloud MaxCompute vs. Heroic vs. Linter vs. mSQL vs. Pinecone

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

RDBMS for high security requirements

mSQL (Mini SQL) is a simple and lightweight RDBMS

A managed, cloud-native vector database

Primary database model

Relational DBMS

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

Time Series DBMS

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

www.alibabacloud.com/product/maxcompute

github.com/spotify/heroic

linter.ru

hughestech.com.au/products/msql

www.pinecone.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

spotify.github.io/heroic

docs.pinecone.io/docs/overview

Developer

Alibaba

Spotify

relex.ru

Hughes Technologies

Pinecone Systems, Inc

Initial release

2016

2014

1990

1994

2019

Current release

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

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

C and C++

Server operating systems

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

Fluentd
Flume
MaxCompute Console

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++
Delphi
Java
Perl
PHP
Tcl

Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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