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

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

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonEsgynDB  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.43
Rank#34  Overall
#20  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Websitespark.apache.org/­sqlwww.esgyn.cnhazelcast.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlhazelcast.org/­imdg/­docs
DeveloperApache Software FoundationEsgynHazelcast
Initial release201420152008
Current release3.5.0 ( 2.13), September 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++, JavaJava
Server operating systemsLinux
OS X
Windows
LinuxAll OS with a Java VM
Data schemeyesyesschema-free
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesJava
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes infoEvent Listeners, Executor Services
Triggersnonoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole-based access control

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More resources
Apache Spark (SQL)EsgynDBHazelcast
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