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DBMS > Google Cloud Bigtable vs. Google Cloud Spanner vs. Riak KV vs. ToroDB

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Spanner vs. Riak KV vs. ToroDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRiak KV  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded 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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Distributed, fault tolerant key-value storeA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelKey-value store
Wide column store
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesDocument 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
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitecloud.google.com/­bigtablecloud.google.com/­spannergithub.com/­torodb/­server
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleGoogleOpenSource, formerly Basho Technologies8Kdata
Initial release2015201720092016
Current release3.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJava
Server operating systemshostedhostedLinux
OS X
All OS with a Java 7 VM
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesnoyes infostring, integer, double, boolean, date, object_id
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.nononono
Secondary indexesnoyesrestricted
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
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
Server-side scripts infoStored proceduresnonoErlang
Triggersnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.selectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyes
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoStrict serializable isolationnono
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.nono
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 roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak SecurityAccess rights for users and roles

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More resources
Google Cloud BigtableGoogle Cloud SpannerRiak KVToroDB
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