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

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonNSDb  Xexclude from comparisonSolr  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 KubernetesA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial 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
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cngithub.com/­hugegraph
hugegraph.apache.org
nsdb.iosolr.apache.orgspark.apache.org/­sql
Technical documentationhugegraph.apache.org/­docsnsdb.io/­Architecturesolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynBaiduApache Software FoundationApache Software Foundation
Initial release20152018201720062014
Current release0.99.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaJava, ScalaJavaScala
Server operating systemsLinuxLinux
macOS
Unix
Linux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes infosupports customizable data types and automatic typingyes
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.nononoyesno
Secondary indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesnoSQL-like query languageSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
WebSocket
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGroovy
Java
Python
Java
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresasynchronous Gremlin script jobsnoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingShardingyes, 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 HBaseyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesvia hugegraph-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers, roles and permissionsyesno

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More resources
EsgynDBHugeGraphNSDbSolrSpark SQL
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