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DBMS > Google Cloud Bigtable vs. Riak KV vs. Vitess vs. WakandaDB

System Properties Comparison Google Cloud Bigtable vs. Riak KV vs. Vitess vs. WakandaDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonRiak KV  Xexclude from comparisonVitess  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, fault tolerant key-value storeScalable, distributed, cloud-native DBMS, extending MySQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelKey-value store
Wide column store
Key-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial 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
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitecloud.google.com/­bigtablevitess.iowakanda.github.io
Technical documentationcloud.google.com/­bigtable/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestvitess.io/­docswakanda.github.io/­doc
DeveloperGoogleOpenSource, formerly Basho TechnologiesThe Linux Foundation, PlanetScaleWakanda SAS
Initial release2015200920132012
Current release3.2.0, December 202215.0.2, December 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache Version 2.0, commercial licenses availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangGoC++, JavaScript
Server operating systemshostedLinux
OS X
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoyesyes
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.nonono
Secondary indexesnorestrictedyes
SQL infoSupport of SQLnonoyes infowith proprietary extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
ADO.NET
JDBC
MySQL protocol
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaScript
Server-side scripts infoStored proceduresnoErlangyes infoproprietary syntaxyes
Triggersnoyes infopre-commit hooks and post-commit hooksyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factorMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storedyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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)yes, using Riak SecurityUsers with fine-grained authorization concept infono user groups or rolesyes

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More resources
Google Cloud BigtableRiak KVVitessWakandaDB
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