DBMS > ClickHouse vs. EJDB vs. LevelDB vs. MongoDB vs. Trino

System Properties Comparison ClickHouse vs. EJDB vs. LevelDB vs. MongoDB vs. Trino

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	410.24
Rank	#5	Overall
	#1	Document stores

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

clickhouse.com

github.com/Softmotions/ejdb

github.com/google/leveldb

www.mongodb.com

trino.io

Technical documentation

clickhouse.com/docs

github.com/Softmotions/ejdb/blob/master/README.md

github.com/google/leveldb/blob/main/doc/index.md

www.mongodb.com/docs/manual

trino.io/broadcast
trino.io/docs/current

Developer

Clickhouse Inc.

Softmotions

Google

MongoDB, Inc

Trino Software Foundation

Initial release

2016

2012

2011

2009

2012

2020 rebranded from PrestoSQL

Current release

v24.6.2.17-stable, July 2024

1.23, February 2021

7.0.5, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

Open Source

BSD

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

server-less

Illumos
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

depending on connected data-source

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

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

in-process shared library

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
RESTful HTTP API
Trino CLI

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

yes, depending on connected data-source

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

depending on connected data-source

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

optional, enabled by default

depending on connected data-source

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

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.

Access rights for users and roles

SQL standard access control

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.