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DBMS > GeoMesa vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. MonetDB vs. RethinkDB

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. MonetDB vs. RethinkDB

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platformA relational database management system that stores data in columnsDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelSpatial DBMSKey-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMSDocument store
Secondary database modelsDocument store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Websitewww.geomesa.orgcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerwww.monetdb.orgrethinkdb.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentationrethinkdb.com/­docs
DeveloperCCRi and othersGoogleMicrosoftMonetDB BVThe Linux Foundation infosince July 2017
Initial release20142015201920042009
Current release4.0.5, February 2024cloud service with continuous releasesDec2023 (11.49), December 20232.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaCC++
Server operating systemshostedhostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes infostring, binary, float, bool, date, geometry
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.nonoyesno
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ryes, in SQL, C, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding infoImplicit feature of the cloud serviceSharding via remote tablesSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none infoSource-replica replication available in experimental statusSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACIDAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoMVCC based
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernonono
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationfine grained access rights according to SQL-standardyes infousers and table-level permissions

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More resources
GeoMesaGoogle Cloud BigtableMicrosoft Azure Data ExplorerMonetDBRethinkDB
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