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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. Apache Phoenix vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. Apache Phoenix vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunephoenix.apache.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software FoundationApache Software Foundation
Initial release2019201720142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedhostedLinux
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infolate-bound, schema-on-read capabilitiesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnononono
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 for high availability, asynchronous replication for up to 15 read replicasMulti-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.Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno

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More resources
Amazon DocumentDBAmazon NeptuneApache PhoenixSpark SQL
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