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DBMS > Google Cloud Datastore vs. ReductStore vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. ReductStore vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docswww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleReductStore LLCApache Software Foundation
Initial release200820232014
Current release1.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, RustScala
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Engineno
TriggersCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflow
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.
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
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)no

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More resources
Google Cloud DatastoreReductStoreSpark SQL
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