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DBMS > Lovefield vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Lovefield vs. Microsoft Azure Table Storage vs. Spark SQL

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable relational database for web apps written in pure JavaScriptA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMicrosoftApache Software Foundation
Initial release201420122014
Current release2.1.12, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptScala
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnono
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languagesJavaScript.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
TriggersUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnono
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesno

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More resources
LovefieldMicrosoft Azure Table StorageSpark SQL
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