DBMS > Alibaba Cloud PolarDB vs. Hive vs. SpatiaLite vs. STSdb

System Properties Comparison Alibaba Cloud PolarDB vs. Hive vs. SpatiaLite vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

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

Spatial extension of SQLite

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.59
Rank	#241	Overall
	#110	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.alibabacloud.com/product/polardb

hive.apache.org

www.gaia-gis.it/fossil/libspatialite/index

github.com/STSSoft/STSdb4

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Alibaba

Apache Software Foundation

initially developed by Facebook

Alessandro Furieri

STS Soft SC

Initial release

2012

2008

2011

Current release

3.1.3, April 2022

5.0.0, August 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GPLv2, commercial license available

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++

Server operating systems

hosted

All OS with a Java VM

server-less

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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 DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift

.NET Client API

Supported programming languages

Java
Python

C++
Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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More resources

DB-Engines blog posts

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