DBMS > Alibaba Cloud PolarDB vs. Apache Druid vs. Netezza vs. RocksDB

System Properties Comparison Alibaba Cloud PolarDB vs. Apache Druid vs. Netezza vs. RocksDB

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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.

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Data warehouse and analytics appliance part of IBM PureSystems

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.59
Rank	#241	Overall
	#110	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.alibabacloud.com/product/polardb

druid.apache.org

www.ibm.com/products/netezza

rocksdb.org

Technical documentation

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

druid.apache.org/docs/latest/design

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Apache Software Foundation and contributors

IBM

Facebook, Inc.

Initial release

2012

2000

2013

Current release

29.0.1, April 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

BSD

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

Linux
OS X
Unix

Linux

included in appliance

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

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 for querying

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
OLE DB

C++ API
Java API

Supported programming languages

Java
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept

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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