DBMS > Alibaba Cloud Table Store vs. Apache Cassandra vs. ClickHouse vs. MongoDB vs. Oracle Berkeley DB

System Properties Comparison Alibaba Cloud Table Store vs. Apache Cassandra vs. ClickHouse vs. MongoDB vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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 in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Vector DBMS

starting with release V5

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

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

www.alibabacloud.com/product/table-store

cassandra.apache.org

clickhouse.com

www.mongodb.com

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

cassandra.apache.org/doc/latest

clickhouse.com/docs

www.mongodb.com/docs/manual

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Alibaba

Apache Software Foundation

Apache top level project, originally developped by Facebook

Clickhouse Inc.

MongoDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2008

2016

2009

1994

Current release

5.0-rc1, July 2024

v24.6.2.17-stable, July 2024

7.0.5, January 2024

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache version 2

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

commercial license available

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

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.

Implementation language

Java

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

BSD
Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

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.

schema-free

Typing

predefined data types such as float or date

yes

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

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

only with the Berkeley DB XML edition

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

Close to ANSI SQL (SQL/JSON + extensions)

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

in MongoDB Atlas only

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

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.

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

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

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

Source-replica replication

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
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-row operations

Atomicity and isolation are supported for single operations

Multi-document ACID Transactions with snapshot isolation

ACID

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

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users can be defined per object

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

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

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

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

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

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