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DBMS > Google Cloud Datastore vs. H2 vs. Spark SQL vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. H2 vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonH2  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSRelational DBMSSearch engine
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
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­datastorewww.h2database.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docswww.h2database.com/­html/­main.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperGoogleThomas MuellerApache Software FoundationSphinx Technologies Inc.
Initial release2008200520142001
Current release2.2.220, July 20233.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence 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 languageJavaScalaC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaJava
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EngineJava Stored Procedures and User-Defined Functionsnono
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosWith clustering: 2 database servers on different computers operate on identical copies of a databasenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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)fine grained access rights according to SQL-standardnono

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More resources
Google Cloud DatastoreH2Spark SQLSphinx
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