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DBMS > GeoMesa vs. Hypertable vs. Microsoft Azure Data Explorer vs. WakandaDB

System Properties Comparison GeoMesa vs. Hypertable vs. Microsoft Azure Data Explorer vs. WakandaDB

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWakandaDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.An open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelSpatial DBMSWide column storeRelational DBMS infocolumn orientedObject oriented DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#356  Overall
#17  Object oriented DBMS
Websitewww.geomesa.orgazure.microsoft.com/­services/­data-explorerwakanda.github.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwakanda.github.io/­doc
DeveloperCCRi and othersHypertable Inc.MicrosoftWakanda SAS
Initial release2014200920192012
Current release5.0.0, May 20240.9.8.11, March 2016cloud service with continuous releases2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGNU version 3. Commercial license availablecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++C++, JavaScript
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
OS X
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
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-typesyes
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.noyesno
Secondary indexesyesrestricted infoonly exact value or prefix value scansall fields are automatically indexed
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsC++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ryes
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernono
User concepts infoAccess controlyes infodepending on the DBMS used for storagenoAzure Active Directory Authenticationyes

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More resources
GeoMesaHypertableMicrosoft Azure Data ExplorerWakandaDB
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