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DBMS > Pinecone vs. Spark SQL vs. TimescaleDB vs. VictoriaMetrics

System Properties Comparison Pinecone vs. Spark SQL vs. TimescaleDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA managed, cloud-native vector databaseSpark 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 fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelVector DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.pinecone.iospark.apache.org/­sqlwww.timescale.comvictoriametrics.com
Technical documentationdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperPinecone Systems, IncApache Software FoundationTimescaleVictoriaMetrics
Initial release2019201420172018
Current release3.5.0 ( 2.13), September 20232.15.0, May 2024v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaCGo
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyes
Typing infopredefined data types such as float or dateString, Number, Booleanyesnumerics, 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.nonoyesno
Secondary indexesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesPythonJava
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 shellno
Triggersnoyesno
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 infoSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
PineconeSpark SQLTimescaleDBVictoriaMetrics
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