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DBMS > etcd vs. FileMaker vs. GeoMesa vs. Microsoft Azure Data Explorer

System Properties Comparison etcd vs. FileMaker vs. GeoMesa vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFileMaker  Xexclude from comparisonGeoMesa  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA distributed reliable key-value storeFileMaker is a cross-platform RDBMS that includes a GUI frontend.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Fully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSSpatial DBMSRelational DBMS infocolumn oriented
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
Score7.05
Rank#53  Overall
#5  Key-value stores
Score45.20
Rank#20  Overall
#14  Relational DBMS
Score0.78
Rank#214  Overall
#4  Spatial DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.claris.com/­filemakerwww.geomesa.orgazure.microsoft.com/­services/­data-explorer
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.claris.com/­resources/­documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperClaris infoa subsidiary of AppleCCRi and othersMicrosoft
Initial release198320142019
Current release3.4, August 201919.4.1, November 20215.0.1, July 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
iOS infoclient part only
Linux
OS X
Windows
hosted
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-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.noyes infoA http query request can return the data in XML formatnoyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infovia pluginsnoKusto Query Language (KQL), SQL subset
APIs and other access methodsgRPC
JSON over HTTP
Filemaker WebDirect
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
PHP.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, R
Triggersyes, watching key changesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnonedepending on storage layerSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Source-replica replication, warm standby infosince Version 14depending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layerEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.nodepending on storage layerno
User concepts infoAccess controlnosimple rights management via user accounts and connection to external directory servicesyes infodepending on the DBMS used for storageAzure Active Directory Authentication

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More resources
etcdFileMakerGeoMesaMicrosoft Azure Data Explorer
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