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DBMS > Hazelcast vs. Spark SQL vs. SWC-DB vs. Transwarp KunDB

System Properties Comparison Hazelcast vs. Spark SQL vs. SWC-DB vs. Transwarp KunDB

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTranswarp KunDB  Xexclude from comparison
DescriptionA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSOLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle
Primary database modelKey-value storeRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score0.10
Rank#344  Overall
#151  Relational DBMS
Websitehazelcast.comspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.transwarp.cn/­en/­product/­kundb
Technical documentationhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHazelcastApache Software FoundationAlex KashirinTranswarp
Initial release200820142020
Current release5.3.6, November 20233.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeschema-freeyesschema-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.yes infothe object must implement a serialization strategynono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnonoyes
Triggersyes infoEventsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole-based access controlnoyes

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More resources
HazelcastSpark SQLSWC-DB infoSuper Wide Column DatabaseTranswarp KunDB
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