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DBMS > GeoMesa vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Stardog

System Properties Comparison GeoMesa vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Stardog

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelSpatial DBMSDocument storeWide column storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.geomesa.orgcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tableswww.stardog.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­datastore/­docsdocs.stardog.com
DeveloperCCRi and othersGoogleMicrosoftStardog-Union
Initial release2014200820122010
Current release5.0.0, May 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaJava
Server operating systemshostedhostedLinux
macOS
Windows
Data schemeyesschema-freeschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like query language (GQL)noYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functions and aggregates, HTTP Server extensions in Java
TriggersnoCallbacks using the Google Apps Enginenoyes infovia event handlers
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 layerMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID
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 layernonoyes
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)Access rights based on private key authentication or shared access signaturesAccess rights for users and roles

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More resources
GeoMesaGoogle Cloud DatastoreMicrosoft Azure Table StorageStardog
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