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DBMS > Datomic vs. Google Cloud Datastore vs. Pinecone vs. RDF4J

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Pinecone vs. RDF4J

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPinecone  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA managed, cloud-native vector databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeVector DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.datomic.comcloud.google.com/­datastorewww.pinecone.iordf4j.org
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docsdocs.pinecone.io/­docs/­overviewrdf4j.org/­documentation
DeveloperCognitectGooglePinecone Systems, IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012200820192004
Current release1.0.7075, December 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava
Server operating systemsAll OS with a Java VMhostedhostedLinux
OS X
Unix
Windows
Data schemeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereString, Number, Booleanyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
PythonJava
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Engineyes
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integritynoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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DatomicGoogle Cloud DatastorePineconeRDF4J infoformerly known as Sesame
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