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DBMS > Databricks vs. Google Cloud Datastore vs. RDF4J vs. STSdb

System Properties Comparison Databricks vs. Google Cloud Datastore vs. RDF4J vs. STSdb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store
Relational DBMS
Document storeRDF storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.72
Rank#222  Overall
#9  RDF stores
Score0.03
Rank#365  Overall
#54  Key-value stores
Websitewww.databricks.comcloud.google.com/­datastorerdf4j.orggithub.com/­STSSoft/­STSdb4
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperDatabricksGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.STS Soft SC
Initial release2013200820042011
Current release4.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#
Server operating systemshostedhostedLinux
OS X
Unix
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infoprimitive types and user defined types (classes)
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.yesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
.NET Client API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C#
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Engineyesno
TriggersCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes 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 integrityyes infovia ReferenceProperties or Ancestor pathsno
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 usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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)nono
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreRDF4J infoformerly known as SesameSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud DatastoreRDF4J infoformerly known as SesameSTSdb
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