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DBMS > Google Cloud Datastore vs. Infobright vs. RethinkDB vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. Infobright vs. RethinkDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonInfobright  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendDBMS 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 processing
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score2.66
Rank#107  Overall
#20  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastoreignitetech.com/­softwarelibrary/­infobrightdbrethinkdb.comspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docsrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleIgnite Technologies Inc.; formerly InfoBright Inc.The Linux Foundation infosince July 2017Apache Software Foundation
Initial release2008200520092014
Current release2.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache Version 2Open Source infoApache 2.0
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 languageCC++Scala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infostring, binary, float, bool, date, geometryyes
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 indexesyesno infoKnowledge Grid Technology used insteadyesno
SQL infoSupport of SQLSQL-like query language (GQL)yesnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
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 proceduresusing Google App Enginenono
TriggersCallbacks using the Google Apps EnginenoClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding inforange basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesyes infousers and table-level permissionsno

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More resources
Google Cloud DatastoreInfobrightRethinkDBSpark SQL
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