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DBMS > ArcadeDB vs. Atos Standard Common Repository vs. Databricks vs. Google Cloud Datastore vs. RDF4J

System Properties Comparison ArcadeDB vs. Atos Standard Common Repository vs. Databricks vs. Google Cloud Datastore vs. RDF4J

Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe 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.
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Key-value store
Document store
Relational DBMS
Document storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitearcadedb.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comcloud.google.com/­datastorerdf4j.org
Technical documentationdocs.arcadedb.comdocs.databricks.comcloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperArcade DataAtos Convergence CreatorsDatabricksGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20212016201320082004
Current releaseSeptember 20211703
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VMLinuxhostedhostedLinux
OS X
Unix
Windows
Data schemeschema-freeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesoptionalyes, details hereyes
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.noyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language, no joinsnowith Databricks SQLSQL-like query language (GQL)no
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
LDAPJDBC
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
Supported programming languagesJavaAll languages with LDAP bindingsPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesusing Google App Engineyes
TriggersyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyesMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate 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 inforelationship in graphsnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
ArcadeDBAtos Standard Common RepositoryDatabricksGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
ArcadeDBAtos Standard Common RepositoryDatabricksGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
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