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DBMS > Amazon Neptune vs. Apache Kylin vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Trafodion

System Properties Comparison Amazon Neptune vs. Apache Kylin vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Trafodion

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Kylin  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, reliable graph database built for the cloudA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTransactional SQL-on-Hadoop DBMS
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeDocument storeRelational 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
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteaws.amazon.com/­neptunekylin.apache.orgfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoretrafodion.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourceskylin.apache.org/­docsfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docstrafodion.apache.org/­documentation.html
DeveloperAmazonApache Software Foundation, originally contributed from eBay IncGoogle infoacquired by Google 2014GoogleApache Software Foundation, originally developed by HP
Initial release20172015201220082014
Current release3.1.0, July 20202.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java
Server operating systemshostedLinuxhostedhostedLinux
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, 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.nonononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)noSQL-like query language (GQL)yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'using Google App EngineJava Stored Procedures
TriggersnoCallbacks are triggered when data changesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
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.Multi-source replication using Paxosyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infousing Google Cloud Dataflowyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate 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 pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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)yes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon NeptuneApache KylinFirebase Realtime DatabaseGoogle Cloud DatastoreTrafodion
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