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DBMS > Google Cloud Bigtable vs. InterSystems Caché vs. Riak TS vs. Teradata Aster

System Properties Comparison Google Cloud Bigtable vs. InterSystems Caché vs. Riak TS vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonRiak TS  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is 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.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application serverRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
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
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websitecloud.google.com/­bigtablewww.intersystems.com/­products/­cache
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.comwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperGoogleInterSystemsOpen Source, formerly Basho TechnologiesTeradata
Initial release2015199720152005
Current release2018.1.4, May 20203.0.0, September 2022
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlang
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Linux
Data schemeschema-freedepending on used data modelschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or datenoyesnoyes
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.noyesnoyes infoin Aster File Store
Secondary indexesnoyesrestrictedyes
SQL infoSupport of SQLnoyesyes, limitedyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesErlangR packages
Triggersnoyesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationselectable replication factoryes 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 methodsyesnoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesno infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableInterSystems CachéRiak TSTeradata Aster
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