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DBMS > GeoMesa vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. RRDtool vs. Vertica

System Properties Comparison GeoMesa vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. RRDtool vs. Vertica

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonRRDtool  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Fully managed big data interactive analytics platformMicrosofts flagship relational DBMSIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelSpatial DBMSRelational DBMS infocolumn orientedRelational DBMSTime Series 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
Document store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.geomesa.orgazure.microsoft.com/­services/­data-explorerwww.microsoft.com/­en-us/­sql-serveross.oetiker.ch/­rrdtoolwww.vertica.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerlearn.microsoft.com/­en-US/­sql/­sql-serveross.oetiker.ch/­rrdtool/­docvertica.com/­documentation
DeveloperCCRi and othersMicrosoftMicrosoftTobias OetikerOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20142019198919992005
Current release5.0.0, May 2024cloud service with continuous releasesSQL Server 2022, November 20221.8.0, 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercial inforestricted free version is availableOpen Source infoGPL V2 and FLOSScommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageScalaC++C infoImplementations in Java (e.g. RRD4J) and C# availableC++
Server operating systemshostedLinux
Windows
HP-UX
Linux
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesNumeric data onlyyes
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.noyesyesno infoExporting into and restoring from XML files possibleno
Secondary indexesyesall fields are automatically indexedyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
in-process shared library
Pipes
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federationnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, but depending on the SQL-Server EditionnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual Consistency
Immediate Consistency
Immediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemonyes
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 layernoyesyesno
User concepts infoAccess controlyes infodepending on the DBMS used for storageAzure Active Directory Authenticationfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GeoMesaMicrosoft Azure Data ExplorerMicrosoft SQL ServerRRDtoolVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
GeoMesaMicrosoft Azure Data ExplorerMicrosoft SQL ServerRRDtoolVertica infoOpenText™ Vertica™
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