DBMS > MongoDB vs. Riak KV vs. TDengine vs. TimesTen

System Properties Comparison MongoDB vs. Riak KV vs. TDengine vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

Distributed, fault tolerant key-value store

Time Series DBMS and big data platform

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Key-value store

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

Time Series DBMS

Relational DBMS

Secondary database models

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

Relational DBMS

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

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.mongodb.com

github.com/taosdata/TDengine
tdengine.com

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

Technical documentation

www.mongodb.com/docs/manual

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

docs.tdengine.com

docs.oracle.com/database/timesten-18.1

Developer

MongoDB, Inc

OpenSource, formerly Basho Technologies

TDEngine, previously Taos Data

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2009

2019

1998

Current release

6.0.7, June 2023

3.2.0, December 2022

3.0, August 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

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, commercial enterprise edition

Open Source

AGPL V3, also commercial editions available

commercial

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.

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.
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Implementation language

C++

Erlang

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

yes

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

Standard SQL with extensions for time-series applications

yes

APIs and other access methods

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP API
Native Erlang Interface

JDBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

JavaScript

Erlang

PL/SQL

Triggers

yes

in MongoDB Atlas only

yes

pre-commit hooks and post-commit hooks

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

Multi-source 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

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

links between data sets can be stored

yes

Transaction concepts

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

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

by means of logfiles and checkpoints

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

yes, using Riak Security

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

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

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

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

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Key customers

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

Market metrics

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

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

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

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Streamlining Time-Series Data Management with TDengine’s PostgreSQL Connector
12 June 2024

Enhancing IoT and Industrial Data Management with TDengine’s MySQL Connector
12 June 2024

Comprehensive Comparison Between TDengine and MongoDB
6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

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