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DBMS > Apache Phoenix vs. Fauna vs. Spark SQL vs. TimescaleDB vs. Transbase

System Properties Comparison Apache Phoenix vs. Fauna vs. Spark SQL vs. TimescaleDB vs. Transbase

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA 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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score1.55
Rank#154  Overall
#26  Document stores
#14  Graph DBMS
#72  Relational DBMS
#13  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitephoenix.apache.orgfauna.comspark.apache.org/­sqlwww.timescale.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationphoenix.apache.orgdocs.fauna.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationFauna, Inc.Apache Software FoundationTimescaleTransaction Software GmbH
Initial release20142014201420171987
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 20232.13.0, November 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaScalaCC and C++
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nononoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationnoneSource-replica replication with hot standby and reads on replicas infoSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononono
User concepts infoAccess controlAccess 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-standardfine grained access rights according to SQL-standard

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More resources
Apache PhoenixFauna infopreviously named FaunaDBSpark SQLTimescaleDBTransbase
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