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DBMS > Apache Spark (SQL) vs. GigaSpaces

System Properties Comparison Apache Spark (SQL) vs. GigaSpaces

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonGigaSpaces  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score1.17
Rank#166  Overall
#27  Document stores
#6  Object oriented DBMS
Websitespark.apache.org/­sqlwww.gigaspaces.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.gigaspaces.com/­latest/­landing.html
DeveloperApache Software FoundationGigaspaces Technologies
Initial release20142000
Current release3.5.0 ( 2.13), September 202315.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; Commercial licenses available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJava, C++, .Net
Server operating systemsLinux
OS X
Windows
Linux
macOS
Solaris
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes
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 infoXML can be used for describing objects metadata
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-99 for query and DML statements
APIs and other access methodsJDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Supported programming languagesJava
Python
R
Scala
.Net
C++
Java
Python
Scala
Server-side scripts infoStored proceduresnoyes
Triggersnoyes, event driven architecture
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.noyes
User concepts infoAccess controlnoRole-based access control

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More resources
Apache Spark (SQL)GigaSpaces
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