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DBMS > FeatureBase vs. Spark SQL vs. TimescaleDB

System Properties Comparison FeatureBase vs. Spark SQL vs. TimescaleDB

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.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 PostgreSQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#325  Overall
#143  Relational DBMS
Score19.78
Rank#36  Overall
#22  Relational DBMS
Score5.62
Rank#73  Overall
#4  Time Series DBMS
Websitewww.featurebase.comspark.apache.org/­sqlwww.timescale.com
Technical documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperMolecula and Pilosa Open Source ContributorsApache Software FoundationTimescale
Initial release201720142017
Current release2022, May 20223.5.0 ( 2.13), September 20232.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC
Server operating systemsLinux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesnonoyes
SQL infoSupport of SQLSQL queriesSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJava
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
FeatureBaseSpark SQLTimescaleDB
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