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DBMS > EsgynDB vs. NSDb vs. Quasardb vs. Spark SQL

System Properties Comparison EsgynDB vs. NSDb vs. Quasardb vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonNSDb  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnnsdb.ioquasar.aispark.apache.org/­sql
Technical documentationnsdb.io/­Architecturedoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynquasardbApache Software Foundation
Initial release2015201720092014
Current release3.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
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++, JavaJava, ScalaC++Scala
Server operating systemsLinuxLinux
macOS
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyes infointeger and binaryyes
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.nononono
Secondary indexesyesall fields are automatically indexedyes infowith tagsno
SQL infoSupport of SQLyesSQL-like query languageSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailno

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More resources
EsgynDBNSDbQuasardbSpark SQL
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