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DBMS > EsgynDB vs. Hazelcast vs. Spark SQL

System Properties Comparison EsgynDB vs. Hazelcast vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnhazelcast.comspark.apache.org/­sql
Technical documentationhazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynHazelcastApache Software Foundation
Initial release201520082014
Current release5.3.6, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScala
Server operating systemsLinuxAll OS with a Java VMLinux
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesno
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyes infoEvent Listeners, Executor Servicesno
Triggersnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoReplicated Mapnone
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 integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedno
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlno

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More resources
EsgynDBHazelcastSpark SQL
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