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DBMS > Amazon Neptune vs. BaseX vs. Google Cloud Datastore vs. Spark SQL vs. Transbase

System Properties Comparison Amazon Neptune vs. BaseX vs. Google Cloud Datastore vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBaseX  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelGraph DBMS
RDF store
Native XML DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websiteaws.amazon.com/­neptunebasex.orgcloud.google.com/­datastorespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.basex.orgcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperAmazonBaseX GmbHGoogleApache Software FoundationTransaction Software GmbH
Initial release20172007200820141987
Current release11.0, June 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC and C++
Server operating systemshostedLinux
OS X
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyes, details hereyesyes
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 indexesnoyesyesnoyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)SQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyesusing Google App Enginenoyes
Triggersnoyes infovia eventsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, 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.noneMulti-source replication using PaxosnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDmultiple readers, single writerACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneBaseXGoogle Cloud DatastoreSpark SQLTransbase
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