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DBMS > Google Cloud Bigtable vs. Quasardb vs. Riak KV vs. SiteWhere

System Properties Comparison Google Cloud Bigtable vs. Quasardb vs. Riak KV vs. SiteWhere

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparisonSiteWhere  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, high-performance timeseries databaseDistributed, fault tolerant key-value storeM2M integration platform for persisting/querying time series data
Primary database modelKey-value store
Wide column store
Time Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.26
Rank#86  Overall
#14  Key-value stores
#6  Wide column stores
Score0.11
Rank#310  Overall
#28  Time Series DBMS
Score6.63
Rank#64  Overall
#8  Key-value stores
Score0.00
Rank#354  Overall
#33  Time Series DBMS
Websitecloud.google.com/­bigtablequasardb.netriak.com/­products/­riak-kvsitewhere.io
Technical documentationcloud.google.com/­bigtable/­docsdoc.quasar.ai/­mastersitewhere.io/­docs/­2.1.0
DeveloperGooglequasardbBasho TechnologiesSiteWhere
Initial release2015200920092010
Current release3.13.3, April 20222.1.0, April 2015
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise editionOpen Source infoCommon Public Attribution License Version 1.0
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 languageC++ErlangJava
Server operating systemshostedBSD
Linux
OS X
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freepredefined scheme
Typing infopredefined data types such as float or datenoyes infointeger and binarynoyes
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 indexesnoyes infowith tagsrestrictedno
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP APIHTTP API
Native Erlang Interface
HTTP REST
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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 proceduresnonoJavaScript and Erlang
Triggersnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingSharding infono "single point of failure"Sharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factorselectable replication factorselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integrationyesno
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
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailnoUsers with fine-grained authorization concept
More information provided by the system vendor
Google Cloud BigtableQuasardbRiak KVSiteWhere
Specific characteristicsHigh-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more
Competitive advantagesHigh performance in a cost-effective small package Real-time results for even large...
» more
Typical application scenariosTick database Predictive maintenance Pre-deal checks Large scale monitoring
» more
Key customersLarge EU investment banks US based hedge funds Orolia Tellmeplus
» more
Market metricsHas been running in very demanding production environments since 2013 Rapid adoption...
» more
Licensing and pricing modelsCommunity edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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Google Cloud BigtableQuasardbRiak KVSiteWhere
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