DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. ClickHouse vs. GeoSpock vs. HBase vs. Spark SQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. ClickHouse vs. GeoSpock vs. HBase vs. Spark SQL

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Spatial and temporal data processing engine for extreme data scale

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

clickhouse.com

geospock.com

hbase.apache.org

spark.apache.org/sql

Technical documentation

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

clickhouse.com/docs

hbase.apache.org/book.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Clickhouse Inc.

GeoSpock

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

Initial release

2016

2008

2014

Current release

v24.4.1.2088-stable, May 2024

2.0, September 2019

2.3.4, January 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Java, Javascript

Java

Scala

Server operating systems

hosted

FreeBSD
Linux
macOS

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

temporal, categorical

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

ANSI SQL for query only (using Presto)

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

key based and custom

Automatic sharding

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication
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

Immediate Consistency or 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)

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 and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per table

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

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