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DBMS > GeoMesa vs. Greenplum vs. Microsoft Azure Synapse Analytics vs. NSDb

System Properties Comparison GeoMesa vs. Greenplum vs. Microsoft Azure Synapse Analytics vs. NSDb

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGreenplum  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelSpatial DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#214  Overall
#4  Spatial DBMS
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Websitewww.geomesa.orggreenplum.orgazure.microsoft.com/­services/­synapse-analyticsnsdb.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.greenplum.orgdocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecture
DeveloperCCRi and othersPivotal Software Inc.Microsoft
Initial release2014200520162017
Current release4.0.5, February 20247.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++Java, Scala
Server operating systemsLinuxhostedLinux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, string
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 infosince Version 4.2nono
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyesyesSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
Supported programming languagesC
Java
Perl
Python
R
C#
Java
PHP
Java
Scala
Server-side scripts infoStored proceduresnoyesTransact SQLno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno 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 datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layerno
User concepts infoAccess controlyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardyes

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More resources
GeoMesaGreenplumMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDb
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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