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DBMS > Atos Standard Common Repository vs. Google Cloud Bigtable vs. InfinityDB vs. RDF4J vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Bigtable vs. InfinityDB vs. RDF4J vs. TigerGraph

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInfinityDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Java embedded Key-Value Store which extends the Java Map interfaceRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Key-value storeRDF storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtableboilerbay.comrdf4j.orgwww.tigergraph.com
Technical documentationcloud.google.com/­bigtable/­docsboilerbay.com/­infinitydb/­manualrdf4j.org/­documentationdocs.tigergraph.com
DeveloperAtos Convergence CreatorsGoogleBoiler Bay Inc.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20162015200220042017
Current release17034.0
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsLinuxhostedAll OS with a Java VMLinux
OS X
Unix
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateoptionalnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.yesnonono
Secondary indexesyesnono infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLnonononoSQL-like query language (GSQL)
APIs and other access methodsLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaJava
PHP
Python
C++
Java
Server-side scripts infoStored proceduresnononoyesyes
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic single-row operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesnonono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoRole-based access control

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More resources
Atos Standard Common RepositoryGoogle Cloud BigtableInfinityDBRDF4J infoformerly known as SesameTigerGraph
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