DBMS > ClickHouse vs. MongoDB vs. NebulaGraph vs. Riak KV vs. Solr

System Properties Comparison ClickHouse vs. MongoDB vs. NebulaGraph vs. Riak KV vs. Solr

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.

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

A distributed, linear scalable, high perfomant Graph DBMS

Distributed, fault tolerant key-value store

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Search engine

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

Spatial DBMS

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

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	2.12
Rank	#125	Overall
	#10	Graph DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	44.28
Rank	#24	Overall
	#3	Search engines

Website

clickhouse.com

www.mongodb.com

github.com/vesoft-inc/nebula
www.nebula-graph.io

solr.apache.org

Technical documentation

clickhouse.com/docs

www.mongodb.com/docs/manual

docs.nebula-graph.io

www.tiot.jp/riak-docs/riak/kv/latest

solr.apache.org/resources.html

Developer

Clickhouse Inc.

MongoDB, Inc

Vesoft Inc.

OpenSource, formerly Basho Technologies

Apache Software Foundation

Initial release

2016

2009

2019

2009

2006

Current release

v23.12.1.1368-stable, December 2023

6.0.7, June 2023

3.2.0, December 2022

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

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 + Common Clause 1.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2

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.

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

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++

Erlang

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

Linux

Linux
OS X

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

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.

Strong typed schema

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

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

yes

supports customizable data types and automatic typing

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

HTTP API
Native Erlang Interface

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
Rust
Scala

3rd party library

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

.Net
C++
Go
Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Erlang

Java plugins

Triggers

yes

in MongoDB Atlas only

yes

pre-commit hooks and post-commit hooks

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

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.

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Causal Clustering using Raft protocol

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

links between data sets can be stored

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

using RocksDB

yes

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

yes

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

Role-based access control

yes, using Riak Security

yes

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

NebulaGraph boasts the world's only graph database solution that is able to host...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Companies from a variety of industries have implemented NebulaGraph Database in production,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more

Licensing and pricing models

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

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

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