DBMS > Microsoft Azure Data Explorer vs. MongoDB vs. ToroDB
System Properties Comparison Microsoft Azure Data Explorer vs. MongoDB vs. ToroDB
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|Editorial information provided by DB-Engines|
|Name||Microsoft Azure Data Explorer Xexclude from comparison||MongoDB Xexclude from comparison||ToroDB Xexclude from comparison|
|Description||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||A MongoDB-compatible JSON document store, built on top of PostgreSQL|
|Primary database model||Relational DBMS column oriented||Document store||Document store|
|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)
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
Search engine integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS Time Series Collections introduced in Release 5.0
|Current release||cloud service with continuous releases||6.0.1, August 2022|
|License Commercial or Open Source||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|
|Cloud-based only Only available as a cloud service||yes||no MongoDB available as DBaaS (MongoDB Atlas)||no|
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|Server operating systems||hosted||Linux|
|All OS with a Java 7 VM|
|Data scheme||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.||schema-free|
|Typing predefined data types such as float or date||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 string, integer, double, boolean, date, object_id|
|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||no|
|Secondary indexes||all fields are automatically indexed||yes|
|SQL Support of SQL||Kusto Query Language (KQL), SQL subset||Read-only SQL queries via the MongoDB Connector for BI|
|APIs and other access methods||Microsoft SQL Server communication protocol (MS-TDS)|
RESTful HTTP API
|proprietary protocol using JSON|
|Supported programming languages||.Net|
|Actionscript unofficial driver|
Clojure unofficial driver
ColdFusion unofficial driver
D unofficial driver
Dart unofficial driver
Delphi unofficial driver
Groovy unofficial driver
Lisp unofficial driver
Lua unofficial driver
MatLab unofficial driver
PowerShell unofficial driver
Prolog unofficial driver
R unofficial driver
Smalltalk unofficial driver
|Triggers||yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy||yes in MongoDB Atlas only||no|
|Partitioning methods Methods for storing different data on different nodes||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|
|Replication methods Methods for redundantly storing data on multiple nodes||yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.||Multi-Source deployments with MongoDB Atlas Global Clusters|
|MapReduce Offers an API for user-defined Map/Reduce methods||Spark connector (open source): github.com/Azure/azure-kusto-spark||yes|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency|
Immediate Consistency can be individually decided for each write operation
|Foreign keys Referential integrity||no||no typically not used, however similar functionality with DBRef possible||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||Multi-document ACID Transactions with snapshot isolation||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||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.||no||yes In-memory storage engine introduced with MongoDB version 3.2|
|User concepts Access control||Azure Active Directory Authentication||Access rights for users and roles||Access rights for users and roles|
|More information provided by the system vendor|
|Microsoft Azure Data Explorer||MongoDB||ToroDB|
|Specific characteristics||Azure Data Explorer is a fast and highly scalable data exploration service for log...|
|Competitive advantages||Kusto Query Language (innovative query language, optimized for high performance data...|
|Typical application scenarios||IoT applications IoT devices generate billions of sensor readings. Normalizing and...|
|Key customers||Microsoft, DocuSign, Taboola, Bosch, Siemens Healthineers, Bühler, Ecolab, Zoomd|
|Market metrics||Azure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...|
|Licensing and pricing models||An Azure Data Explorer cluster is a pair of engine and data management clusters which...|
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|Microsoft Azure Data Explorer||MongoDB||ToroDB|
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