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DBMS > Datomic vs. Google Cloud Bigtable vs. Teradata Aster vs. Valentina Server

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Teradata Aster vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTeradata Aster  Xexclude from comparisonValentina Server  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle'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 typesObject-relational database and reports server
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.datomic.comcloud.google.com/­bigtablewww.valentina-db.net
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectGoogleTeradataParadigma Software
Initial release2012201520051999
Current release1.0.6735, June 20235.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, Clojure
Server operating systemsAll OS with a Java VMhostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
OLE DB
ODBC
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoR packagesyes
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DatomicGoogle Cloud BigtableTeradata AsterValentina Server
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