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DBMS > Google Cloud Datastore vs. Greenplum vs. LevelDB vs. Microsoft Azure AI Search vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. Greenplum vs. LevelDB vs. Microsoft Azure AI Search vs. RDF4J

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically 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 valuesSearch-as-a-service for web and mobile app developmentRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeRelational DBMSKey-value storeSearch engineRDF store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score5.52
Rank#59  Overall
#6  Search engines
Score0.74
Rank#222  Overall
#9  RDF stores
Websitecloud.google.com/­datastoregreenplum.orggithub.com/­google/­leveldbazure.microsoft.com/­en-us/­services/­searchrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.greenplum.orggithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­en-us/­azure/­searchrdf4j.org/­documentation
DeveloperGooglePivotal Software Inc.GoogleMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20082005201120152004
Current release7.0.0, September 20231.23, February 2021V1
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSDcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedLinuxIllumos
Linux
OS X
Windows
hostedLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereyesnoyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP APIJava 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
C#
Java
JavaScript
Python
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyesnonoyes
TriggersCallbacks using the Google Apps Engineyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnoneyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoyes infousing Azure authenticationno

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More resources
Google Cloud DatastoreGreenplumLevelDBMicrosoft Azure AI SearchRDF4J infoformerly known as Sesame
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