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DBMS > Google Cloud Datastore vs. ObjectBox vs. Stardog vs. Titan

System Properties Comparison Google Cloud Datastore vs. ObjectBox vs. Stardog vs. Titan

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparisonStardog  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformExtremely fast embedded database for small devices, IoT and MobileEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument storeObject oriented DBMSGraph DBMS
RDF store
Graph DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­datastoreobjectbox.iowww.stardog.comgithub.com/­thinkaurelius/­titan
Technical documentationcloud.google.com/­datastore/­docsdocs.objectbox.iodocs.stardog.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperGoogleObjectBox LimitedStardog-UnionAurelius, owned by DataStax
Initial release2008201720102012
Current release7.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaJava
Server operating systemshostedAndroid
iOS
Linux
macOS
Windows
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL-like query language (GQL)noYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Clojure
Java
Python
Server-side scripts infoStored proceduresusing Google App Enginenouser defined functions and aggregates, HTTP Server extensions in Javayes
TriggersCallbacks using the Google Apps Enginenoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosonline/offline synchronization between client and serverMulti-source replication in HA-Clusteryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes infovia Faunus, a graph analytics engine
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 Consistency in HA-ClusterEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes inforelationships in graphsyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAccess rights for users and rolesUser authentification and security via Rexster Graph Server
More information provided by the system vendor
Google Cloud DatastoreObjectBoxStardogTitan
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More resources
Google Cloud DatastoreObjectBoxStardogTitan
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