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DBMS > GeoMesa vs. Google Cloud Datastore vs. Greenplum vs. LevelDB vs. RDF4J

System Properties Comparison GeoMesa vs. Google Cloud Datastore vs. Greenplum vs. LevelDB vs. RDF4J

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonLevelDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 PlatformAnalytic 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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelSpatial DBMSDocument storeRelational DBMSKey-value storeRDF store
Secondary database modelsDocument store
Spatial DBMS
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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.geomesa.orgcloud.google.com/­datastoregreenplum.orggithub.com/­google/­leveldbrdf4j.org
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­datastore/­docsdocs.greenplum.orggithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentation
DeveloperCCRi and othersGooglePivotal Software Inc.GoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20142008200520112004
Current release5.0.0, May 20247.0.0, September 20231.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache 2.0Open Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++Java
Server operating systemshostedLinuxIllumos
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereyesnoyes
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.nonoyes infosince Version 4.2no
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Engineyesnoyes
TriggersnoCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerMulti-source replication using PaxosSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyesnono
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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernono
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)fine grained access rights according to SQL-standardnono

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More resources
GeoMesaGoogle Cloud DatastoreGreenplumLevelDBRDF4J infoformerly known as Sesame
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