DBMS > Blueflood vs. ClickHouse vs. MongoDB vs. Oracle vs. ScyllaDB

System Properties Comparison Blueflood vs. ClickHouse vs. MongoDB vs. Oracle vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Widely used RDBMS

Cassandra and DynamoDB compatible wide column store

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
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Key-value store

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

blueflood.io

clickhouse.com

www.mongodb.com

www.oracle.com/database

www.scylladb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

clickhouse.com/docs

www.mongodb.com/docs/manual

docs.oracle.com/en/database

docs.scylladb.com

Developer

Rackspace

Clickhouse Inc.

MongoDB, Inc

Oracle

ScyllaDB

Initial release

2013

2016

2009

1980

2015

Current release

v24.4.1.2088-stable, May 2024

6.0.7, June 2023

23c, September 2023

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

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.

commercial

restricted free version is available

Open Source

Open Source (AGPL), commercial license available

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.

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.

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.
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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Java

C++

C and C++

C++

Server operating systems

Linux
OS X

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

predefined 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

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

APIs and other access methods

HTTP REST

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
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

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

yes

JavaScript

PL/SQL

also stored procedures in Java possible

yes, Lua

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

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, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

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

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

isolation level can be parameterized

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

in-memory tables

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

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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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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