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DBMS > Google Cloud Datastore vs. JaguarDB vs. Lovefield vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. JaguarDB vs. Lovefield vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJaguarDB  Xexclude from comparisonLovefield  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPerformant, highly scalable DBMS for AI and IoT applicationsEmbeddable relational database for web apps written in pure JavaScriptOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeKey-value store
Vector DBMS
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.06
Rank#381  Overall
#59  Key-value stores
#15  Vector DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­datastorewww.jaguardb.comgoogle.github.io/­lovefieldsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docswww.jaguardb.com/­support.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsphinxsearch.com/­docs
DeveloperGoogleDataJaguar, Inc.GoogleSphinx Technologies Inc.
Initial release2008201520142001
Current release3.3 July 20232.1.12, February 20173.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open 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 languageC++ infothe server part. Clients available in other languagesJavaScriptC++
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
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 indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like query language infovia JavaScript builder patternSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Enginenonono
TriggersCallbacks using the Google Apps EnginenoUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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.Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes 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.nonoyes infousing MemoryDB
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsnono

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More resources
Google Cloud DatastoreJaguarDBLovefieldSphinx
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