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DBMS > GeoMesa vs. GridDB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage

System Properties Comparison GeoMesa vs. GridDB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Scalable in-memory time series database optimized for IoT and Big DataElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelSpatial DBMSTime Series DBMSRelational DBMSWide column store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitewww.geomesa.orggriddb.netazure.microsoft.com/­services/­synapse-analyticsazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.griddb.netdocs.microsoft.com/­azure/­synapse-analytics
DeveloperCCRi and othersToshiba CorporationMicrosoftMicrosoft
Initial release2014201320162012
Current release5.0.0, May 20245.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++
Server operating systemsLinuxhostedhosted
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonoTransact SQLno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding, horizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerSource-replica replicationyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDoptimistic locking
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 layeryesno
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users can be defined per databaseyesAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
GeoMesaGridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMicrosoft Azure Table Storage
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
GeoMesaGridDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMicrosoft Azure Table Storage
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