DBMS > ClickHouse vs. HEAVY.AI vs. Hive vs. Lovefield vs. searchxml

System Properties Comparison ClickHouse vs. HEAVY.AI vs. Hive vs. Lovefield vs. searchxml

Editorial information provided by DB-Engines

Name

Description

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable relational database for web apps written in pure JavaScript

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Native XML DBMS
Search engine

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

clickhouse.com

github.com/heavyai/heavydb
www.heavy.ai

hive.apache.org

google.github.io/lovefield

www.searchxml.net/category/products

Technical documentation

clickhouse.com/docs

docs.heavy.ai

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/lovefield/blob/master/docs/spec_index.md

www.searchxml.net/support/handouts

Developer

Clickhouse Inc.

HEAVY.AI, Inc.

Apache Software Foundation

initially developed by Facebook

Google

informationpartners gmbh

Initial release

2016

2012

2014

2015

Current release

v24.4.1.2088-stable, May 2024

5.10, January 2022

3.1.3, April 2022

2.1.12, February 2017

1.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

C++ and CUDA

Java

JavaScript

C++

Server operating systems

FreeBSD
Linux
macOS

Linux

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Windows

Data scheme

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
Thrift

RESTful HTTP API
WebDAV
XQuery
XSLT

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

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
PHP
Python

JavaScript

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

on the application server

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

selectable replication factor

none

yes

sychronisation to multiple collections

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

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.

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Domain, group and role-based access control at the document level and for application services

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