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DBMS > Atos Standard Common Repository vs. Google Cloud Bigtable vs. Teradata Aster vs. TigerGraph vs. WakandaDB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Bigtable vs. Teradata Aster vs. TigerGraph vs. WakandaDB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTigerGraph  Xexclude from comparisonWakandaDB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore 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.Platform for big data analytics on multistructured data sources and typesA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Relational DBMSGraph DBMSObject oriented 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
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.tigergraph.comwakanda.github.io
Technical documentationcloud.google.com/­bigtable/­docsdocs.tigergraph.comwakanda.github.io/­doc
DeveloperAtos Convergence CreatorsGoogleTeradataWakanda SAS
Initial release20162015200520172012
Current release17032.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, JavaScript
Server operating systemsLinuxhostedLinuxLinuxLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyesyes
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.yesnoyes infoin Aster File Storenono
Secondary indexesyesnoyes
SQL infoSupport of SQLnonoyesSQL-like query language (GSQL)no
APIs and other access methodsLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
C++
Java
JavaScript
Server-side scripts infoStored proceduresnonoR packagesyesyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoSQL Map-Reduce Frameworkyesno
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole-based access controlyes

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More resources
Atos Standard Common RepositoryGoogle Cloud BigtableTeradata AsterTigerGraphWakandaDB
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