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DBMS > Amazon Neptune vs. Firebird vs. Hive vs. Spark SQL vs. Trafodion

System Properties Comparison Amazon Neptune vs. Firebird vs. Hive vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFirebird  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  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 cloudFirebird is an open source RDBMS forked from Borland's InterBasedata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational 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
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.firebirdsql.orghive.apache.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.firebirdsql.org/­en/­reference-manualscwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperAmazonFirebird FoundationApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation, originally developed by HP
Initial release20172000 infoAs fork of Borland's InterBase201220142014
Current release5.0.0, January 20243.1.3, April 20223.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaScalaC++, Java
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
All OS with a Java VMLinux
OS X
Windows
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JDBC
ODBC
Thrift
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoPSQLyes infouser defined functions and integration of map-reducenoJava Stored Procedures
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, utilizing Spark CoreSharding
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.Source-replica replicationselectable replication factornoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyesyes
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.nono
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 conceptAccess rights for users, groups and rolesnofine grained access rights according to SQL-standard

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Amazon NeptuneFirebirdHiveSpark SQLTrafodion
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