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DBMS > EsgynDB vs. HugeGraph vs. Microsoft Azure SQL Database vs. NSDb vs. Spark SQL

System Properties Comparison EsgynDB vs. HugeGraph vs. Microsoft Azure SQL Database vs. NSDb vs. Spark SQL

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  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 DBMSDatabase as a Service offering with high compatibility to Microsoft SQL ServerScalable, 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 DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cngithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­products/­azure-sql/­databasensdb.iospark.apache.org/­sql
Technical documentationhugegraph.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynBaiduMicrosoftApache Software Foundation
Initial release20152018201020172014
Current release0.9V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaC++Java, ScalaScala
Server operating systemsLinuxLinux
macOS
Unix
hostedLinux
macOS
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes: 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.nonoyesnono
Secondary indexesyesyes infoalso supports composite index and range indexyesall fields are automatically indexedno
SQL infoSupport of SQLyesnoyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGroovy
Java
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresasynchronous Gremlin script jobsTransact SQLnono
Triggersnonoyesno
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 HBaseyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infoedges in graphyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing 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 permissionsfine grained access rights according to SQL-standardno

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More resources
EsgynDBHugeGraphMicrosoft Azure SQL Database infoformerly SQL AzureNSDbSpark SQL
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