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DBMS > Apache Spark (SQL) vs. Hazelcast vs. MySQL

System Properties Comparison Apache Spark (SQL) vs. Hazelcast vs. MySQL

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonHazelcast  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingA widely adopted in-memory data gridWidely used open source RDBMS
Primary database modelRelational DBMSKey-value storeRelational DBMS infoKey/Value like access via memcached API
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score5.58
Rank#57  Overall
#6  Key-value stores
Score964.98
Rank#2  Overall
#2  Relational DBMS
Websitespark.apache.org/­sqlhazelcast.comwww.mysql.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlhazelcast.org/­imdg/­docsdev.mysql.com/­doc
DeveloperApache Software FoundationHazelcastOracle infosince 2010, originally MySQL AB, then Sun
Initial release201420081995
Current release3.5.0 ( 2.13), September 20235.3.6, November 20239.0.0, July 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaC and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMFreeBSD
Linux
OS X
Solaris
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.noyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava
Python
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax
Triggersnoyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoRole-based access controlUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache Spark (SQL)HazelcastMySQL
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