DBMS > Apache IoTDB vs. Microsoft Azure Data Explorer vs. MongoDB vs. TDengine vs. TDSQL for MySQL
System Properties Comparison Apache IoTDB vs. Microsoft Azure Data Explorer vs. MongoDB vs. TDengine vs. TDSQL for MySQL
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Name | Apache IoTDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | MongoDB Xexclude from comparison | TDengine Xexclude from comparison | TDSQL for MySQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | Fully managed big data interactive analytics platform | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Time Series DBMS and big data platform | A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series DBMS | Relational DBMS column oriented | Document store | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | 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 | Document store Spatial DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | iotdb.apache.org | azure.microsoft.com/services/data-explorer | www.mongodb.com | github.com/taosdata/TDengine tdengine.com | www.tencentcloud.com/products/dcdb | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | docs.microsoft.com/en-us/azure/data-explorer | www.mongodb.com/docs/manual | docs.tdengine.com | www.tencentcloud.com/document/product/1042 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation | Microsoft | MongoDB, Inc | TDEngine, previously Taos Data | Tencent | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 2019 | 2009 | 2019 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.1.0, April 2023 | cloud service with continuous releases | 6.0.7, June 2023 | 3.0, August 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | commercial | 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 AGPL V3, also commercial editions available | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no MongoDB available as DBaaS (MongoDB Atlas) | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM (>= 1.8) | hosted | Linux OS X Solaris Windows | Linux Windows | hosted | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | Fixed schema with schema-less datatypes (dynamic) | 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 | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes string, integer, double, decimal, boolean, date, object_id, geospatial | yes | 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. | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | Kusto Query Language (KQL), SQL subset | Read-only SQL queries via the MongoDB Atlas SQL Interface | Standard SQL with extensions for time-series applications | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Native API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | JDBC RESTful HTTP API | JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Go Java Python Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | 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++ Go Java JavaScript (Node.js) PHP Python Rust | C C# C++ Java PHP Python Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | Yes, possible languages: KQL, Python, R | JavaScript | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes in MongoDB Atlas only | yes, via alarm monitoring | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | Sharding Implicit feature of the cloud service | 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 | Automatic sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | yes | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Integration with Hadoop and Spark | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Strong Consistency with Raft | Eventual Consistency Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no typically not used, however similar functionality with DBRef possible | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no | Multi-document ACID Transactions with snapshot isolation | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optional, enabled by default | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes In-memory storage engine introduced with MongoDB version 3.2 | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | Azure Active Directory Authentication | Access rights for users and roles | yes | Users with fine-grained authorization concept | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache IoTDB | Microsoft Azure Data Explorer | MongoDB | TDengine | TDSQL for MySQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | TDengineā¢ is a next generation data historian purpose-built for Industry 4.0 and... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Can Typical Time-Series Databases Replace Data Historians? TDengine 3.3.0.0 Release Notes How to Unlock Value from Industrial Data with AI and ML Technology Compare InfluxDB vs. TDengine Why We Need the Next Generation Data Historian | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache IoTDB | Microsoft Azure Data Explorer | MongoDB | TDengine | TDSQL for MySQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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