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DBMS > Apache IoTDB vs. Microsoft Azure Table Storage vs. MongoDB vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Microsoft Azure Table Storage vs. MongoDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMongoDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA lightweight IoT native database management system deployable on the device and syncing the collected data with the cloud and integrated with Hadoop and SparkA Wide Column Store for rapid development using massive semi-structured datasetsOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSWide column storeDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.18
Rank#290  Overall
#24  Time Series DBMS
Score5.25
Rank#71  Overall
#5  Wide column stores
Score493.55
Rank#5  Overall
#1  Document stores
Score3.96
Rank#84  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.mongodb.comwww.timescale.com
Technical documentationdocs.mongodb.com/­manualdocs.timescale.com
DeveloperApache Software FoundationMicrosoftMongoDB, IncTimescale
Initial release2018201220092017
Current release5.0, July 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infoAlthough 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 infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoRead-only SQL queries via the MongoDB Connector for BIyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCRESTful HTTP APIproprietary protocol using JSONADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoJavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes infoin MongoDB Atlas onlyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency with synchronizing with the cloudImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBMicrosoft Azure Table StorageMongoDBTimescaleDB
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» more
Timescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesThe MongoDB platform can be used by developers building transactional, operational,...
» more
TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
DevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
TransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more
Market metrics175 million downloads, over 1.5M Atlas database clusters under management handling...
» more
With over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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More resources
Apache IoTDBMicrosoft Azure Table StorageMongoDBTimescaleDB
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London, 9 November 2021

Finished events

Introduction to MongoDB
Webinar, on demand, 27 July 2021 (finished)

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Apache IoTDB now a Top-Level Project at ASF
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