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DBMS > Spark SQL vs. TimescaleDB

System Properties Comparison Spark SQL vs. TimescaleDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionSpark 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 DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score23.33
Rank#33  Overall
#19  Relational DBMS
Score4.33
Rank#84  Overall
#5  Time Series DBMS
Websitespark.apache.org/­sqlwww.timescale.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperApache Software FoundationTimescale
Initial release20142017
Current release3.2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesnumerics, 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.noyes
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJava
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
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-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 integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
Spark SQLTimescaleDB
Specific characteristicsTimescale is the creator of TimescaleDB , the first open-source relational database...
» more
Competitive advantagesTimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more
Typical application scenariosDevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more
Key customersTransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more
Market metricsWith over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
» more
Licensing and pricing modelsTimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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More resources
Spark SQLTimescaleDB
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