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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonMemcached  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.In-memory key-value store, originally intended for cachingRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeSearch engineKey-value storeRDF 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
Score19.42
Rank#32  Overall
#4  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastoremanticoresearch.comwww.memcached.orgrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsmanual.manticoresearch.comgithub.com/­memcached/­memcached/­wikirdf4j.org/­documentation
DeveloperGoogleManticore SoftwareDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720032004
Current release6.0, February 20231.6.27, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Open Source infoBSD licenseOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemshostedFreeBSD
Linux
macOS
Windows
FreeBSD
Linux
OS X
Unix
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, Booleannoyes
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 XML
Secondary indexesyesyes infofull-text index on all search fieldsnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languagenono
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
Proprietary protocolJava 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++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
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 supportednonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSynchronous replication based on Galera librarynone infoRepcached, a Memcached patch, provides this functionallitynone
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.
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 writesnoACID 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.noyes 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.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
Google Cloud DatastoreManticore SearchMemcachedRDF4J infoformerly known as Sesame
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