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DBMS > Amazon Neptune vs. Badger vs. BaseX vs. NSDb vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Badger vs. BaseX vs. NSDb vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBadger  Xexclude from comparisonBaseX  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Scalable, 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 modelGraph DBMS
RDF store
Key-value storeNative XML DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­dgraph-io/­badgerbasex.orgnsdb.iospark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgodoc.org/­github.com/­dgraph-io/­badgerdocs.basex.orgnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonDGraph LabsBaseX GmbHApache Software Foundation
Initial release20172017200720172014
Current release10.7, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoBSD licenseOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJava, ScalaScala
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnono infoXQuery supports typesyes: 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 indexesnonoyesall fields are automatically indexedno
SQL infoSupport of SQLnononoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
GoActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonoyes infovia eventsno
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnomultiple readers, single writernono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noUsers with fine-grained authorization concept on 4 levelsno

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More resources
Amazon NeptuneBadgerBaseXNSDbSpark SQL
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