DBMS > ClickHouse vs. Lovefield vs. OrientDB

System Properties Comparison ClickHouse vs. Lovefield vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

Embeddable relational database for web apps written in pure JavaScript

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Time Series DBMS

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

Score	13.18
Rank	#46	Overall
	#30	Relational DBMS

Score	0.25
Rank	#281	Overall
	#133	Relational DBMS

Score	5.21
Rank	#78	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores

Website

clickhouse.tech

google.github.io/lovefield

orientdb.org

Technical documentation

clickhouse.tech/docs

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

www.orientdb.com/docs/last/index.html

Developer

Clickhouse Inc.

Google

OrientDB LTD; CallidusCloud; SAP

Initial release

2016

2014

2010

Current release

v22.7.2.15-stable, August 2022

2.1.12, February 2017

3.1.9, February 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache version 2

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.

Implementation language

C++

JavaScript

Java

Server operating systems

FreeBSD
Linux
macOS

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language, no joins

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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
Scala

3rd party library

JavaScript

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java, Javascript

Triggers

Using read-only observers

Hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

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

Access rights for users and roles; record level security configurable

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Prague-based Better Stack raises €18.2M to provide an improved observability stack for developers
22 July 2022, Silicon Canals

Two Sizes Fit Most: PostgreSQL and ClickHouse – The New Stack
13 April 2022, thenewstack.io

Multiple Flaws Uncovered in ClickHouse OLAP Database System for Big Data
16 March 2022, The Hacker News

ClickHouse Raises $250M Series B To Scale Groundbreaking OLAP Database Management System Globally
28 October 2021, Business Wire

Intel Xeon Platinum 8380 “Ice Lake” CPU Shows Great Improvement In Linux 6.0
15 August 2022, Wccftech

provided by Google News

CallidusCloud Acquires Leading Multi-Model Database Technology
19 September 2017, GlobeNewswire

The 12 Best Graph Databases to Consider for 2022
22 December 2021, Solutions Review

The untapped potential of HPC + graph computing
30 October 2021, VentureBeat

What are graph database query languages?
3 September 2021, VentureBeat

NoSQL Databases | When to Use NoSQL vs SQL
19 January 2022, Server Watch

provided by Google News

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