DBMS > Amazon CloudSearch vs. ClickHouse vs. HarperDB vs. HBase

System Properties Comparison Amazon CloudSearch vs. ClickHouse vs. HarperDB vs. HBase

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Website

aws.amazon.com/cloudsearch

clickhouse.com

www.harperdb.io

hbase.apache.org

Technical documentation

docs.aws.amazon.com/cloudsearch

clickhouse.com/docs

docs.harperdb.io/docs

hbase.apache.org/book.html

Developer

Amazon

Clickhouse Inc.

HarperDB

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2012

2016

2017

2008

Current release

v24.4.1.2088-stable, May 2024

3.1, August 2021

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free community edition available

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Node.js

Java

Server operating systems

hosted

FreeBSD
Linux
macOS

Linux
OS X

Linux
Unix
Windows

using Cygwin

Data scheme

yes

dynamic schema

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

JSON data types

options to bring your own types, AVRO

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like data manipulation statements

APIs and other access methods

HTTP API

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RESTful HTTP API
Thrift

Supported programming languages

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

key based and custom

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

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

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

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

Transaction concepts

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

Atomic execution of specific operations

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

authentication via encrypted signatures

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 and roles

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

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