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

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA fast-speed and highly-scalable Graph DBMSScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.21
Rank#288  Overall
#134  Relational DBMS
Score0.22
Rank#286  Overall
#22  Graph DBMS
Score0.00
Rank#354  Overall
#33  Time Series DBMS
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websitewww.esgyn.cngithub.com/­hugegraphnsdb.iospark.apache.org/­sql
Technical documentationhugegraph.github.io/­hugegraph-docnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynBaiduApache Software Foundation
Initial release2015201820172014
Current release0.93.2.0, October 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaJava, ScalaScala
Server operating systemsLinuxLinux
macOS
Unix
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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 indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedno
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGroovy
Java
Python
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresasynchronous Gremlin script jobsnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
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-standardUsers, roles and permissionsno

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EsgynDBHugeGraphNSDbSpark SQL
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