DBMS > Alibaba Cloud PolarDB vs. Apache Impala vs. Derby

System Properties Comparison Alibaba Cloud PolarDB vs. Apache Impala vs. Derby

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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.

Analytic DBMS for Hadoop

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

Primary database model

Relational DBMS

Secondary database models

Document store

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

Score	0.59
Rank	#241	Overall
	#110	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Website

www.alibabacloud.com/product/polardb

impala.apache.org

db.apache.org/derby

Technical documentation

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

impala.apache.org/impala-docs.html

db.apache.org/derby/manuals/index.html

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Initial release

2013

1997

Current release

4.1.0, June 2022

10.17.1.0, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache version 2

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++

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Data scheme

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

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

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

Source-replica replication

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

Immediate 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

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Licensing and pricing models

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