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DBMS > Google Cloud Datastore vs. Manticore Search vs. Quasardb vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. Manticore Search vs. Quasardb vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.Distributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeSearch engineTime Series DBMSRDF store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.22
Rank#312  Overall
#21  Search engines
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastoremanticoresearch.comquasar.airdf4j.org
Technical documentationcloud.google.com/­datastore/­docsmanual.manticoresearch.comdoc.quasar.ai/­masterrdf4j.org/­documentation
DeveloperGoogleManticore SoftwarequasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720092004
Current release6.0, February 20233.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java
Server operating systemshostedFreeBSD
Linux
macOS
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeFixed schemaschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infointeger and binaryyes
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.noCan index from XMLno
Secondary indexesyesyes infofull-text index on all search fieldsyes infowith tagsyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
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
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoyes
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSynchronous replication based on Galera librarySource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownowith Hadoop integrationno
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yes infoby using LevelDByes 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.noyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noCryptographically strong user authentication and audit trailno

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Google Cloud DatastoreManticore SearchQuasardbRDF4J infoformerly known as Sesame
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