DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. HBase vs. Netezza vs. OpenSearch vs. Solr

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. HBase vs. Netezza vs. OpenSearch vs. Solr

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Wide-column store based on Apache Hadoop and on concepts of BigTable

Data warehouse and analytics appliance part of IBM PureSystems

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Vector DBMS

Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/hybriddb-postgresql

hbase.apache.org

www.ibm.com/products/netezza

github.com/opensearch-project
opensearch.org

solr.apache.org

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

hbase.apache.org/book.html

opensearch.org/docs/latest

solr.apache.org/resources.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM

Amazon Web Services

Apache Software Foundation

Initial release

2016

2008

2000

2021

2006

Current release

2.3.4, January 2021

2.5.0, January 2023

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux

included in appliance

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Java plugins

Triggers

yes

by using the 'percolation' feature

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

optimistic locking

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

yes

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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