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DBMS > EsgynDB vs. JaguarDB vs. Spark SQL vs. Typesense

System Properties Comparison EsgynDB vs. JaguarDB vs. Spark SQL vs. Typesense

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionPerformant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processingA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSKey-value store
Vector DBMS
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.79
Rank#210  Overall
#14  Search engines
Websitewww.esgyn.cnwww.jaguardb.comspark.apache.org/­sqltypesense.org
Technical documentationwww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypesense.org/­docs
DeveloperEsgynDataJaguar, Inc.Apache Software Foundation
Initial release2015201520142015
Current release3.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++ infothe server part. Clients available in other languagesScalaC++
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
Data schemeyesyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnonono
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 datacentersMulti-source replicationnoneMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsno

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More resources
EsgynDBJaguarDBSpark SQLTypesense
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