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DBMS > Amazon Neptune vs. FoundationDB vs. Google Cloud Datastore vs. Hive

System Properties Comparison Amazon Neptune vs. FoundationDB vs. Google Cloud Datastore vs. Hive

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionFast, reliable graph database built for the cloudOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelGraph DBMS
RDF store
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document storeRelational 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
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­apple/­foundationdbcloud.google.com/­datastorehive.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesapple.github.io/­foundationdbcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAmazonFoundationDBGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2017201320082012
Current release6.2.28, November 20203.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedLinux
OS X
Windows
hostedAll OS with a Java VM
Data schemeschema-freeschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyes, details hereyes
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.nono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnosupported in specific SQL layer onlySQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoin SQL-layer onlyusing Google App Engineyes infouser defined functions and integration of map-reduce
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
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.yesMulti-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable 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.Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsin SQL-layer onlyyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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More resources
Amazon NeptuneFoundationDBGoogle Cloud DatastoreHive
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