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DBMS > Google Cloud Bigtable vs. RethinkDB vs. Spark SQL vs. Yaacomo

System Properties Comparison Google Cloud Bigtable vs. RethinkDB vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is 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.DBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelKey-value store
Wide column store
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score2.74
Rank#105  Overall
#19  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­bigtablerethinkdb.comspark.apache.org/­sqlyaacomo.com
Technical documentationcloud.google.com/­bigtable/­docsrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleThe Linux Foundation infosince July 2017Apache Software FoundationQ2WEB GmbH
Initial release2015200920142009
Current release2.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes infostring, binary, float, bool, date, geometryyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
TriggersnoClient-side triggers through changefeedsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding inforange basedyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic single-document operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyesyes
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousers and table-level permissionsnofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableRethinkDBSpark SQLYaacomo
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