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DBMS > Google Cloud Datastore vs. Manticore Search vs. RDF4J vs. TDSQL for MySQL

System Properties Comparison Google Cloud Datastore vs. Manticore Search vs. RDF4J vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelDocument storeSearch engineRDF storeRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument store
Spatial DBMS
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
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitecloud.google.com/­datastoremanticoresearch.comrdf4j.orgwww.tencentcloud.com/­products/­dcdb
Technical documentationcloud.google.com/­datastore/­docsmanual.manticoresearch.comrdf4j.org/­documentationwww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleManticore SoftwareSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Tencent
Initial release2008201720042013
Current release6.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Open Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedFreeBSD
Linux
macOS
Windows
Linux
OS X
Unix
Windows
hosted
Data schemeschema-freeFixed schemayes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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 fieldsyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languagenoyes
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
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
PHP
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyesyes
TriggersCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednoneAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSynchronous replication based on Galera librarynoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 writesACID infoIsolation support depends on the API usedACID
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 infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoUsers with fine-grained authorization concept

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More resources
Google Cloud DatastoreManticore SearchRDF4J infoformerly known as SesameTDSQL for MySQL
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