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DBMS > Amazon Neptune vs. Apache Phoenix vs. Fauna vs. Spark SQL vs. Transbase

System Properties Comparison Amazon Neptune vs. Apache Phoenix vs. Fauna vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Spark 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
Relational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteaws.amazon.com/­neptunephoenix.apache.orgfauna.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orgdocs.fauna.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperAmazonApache Software FoundationFauna, Inc.Apache Software FoundationTransaction Software GmbH
Initial release20172014201420141987
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen 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 languageJavaScalaScalaC and C++
Server operating systemshostedLinux
Unix
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsnoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoconsistent hashingyes, 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.Multi-source replication
Source-replica replication
Multi-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoyes
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.yesnonono
User concepts infoAccess controlAccess 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-tenancyIdentity management, authentication, and access controlnofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneApache PhoenixFauna infopreviously named FaunaDBSpark SQLTransbase
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