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DBMS > Pinecone vs. PostgreSQL vs. Solr vs. Spark SQL vs. Sqrrl

System Properties Comparison Pinecone vs. PostgreSQL vs. Solr vs. Spark SQL vs. Sqrrl

Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA managed, cloud-native vector databaseWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelVector DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.pinecone.iowww.postgresql.orgsolr.apache.orgspark.apache.org/­sqlsqrrl.com
Technical documentationdocs.pinecone.io/­docs/­overviewwww.postgresql.org/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperPinecone Systems, IncPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software FoundationApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release20191989 info1989: Postgres, 1996: PostgreSQL200620142012
Current release16.3, May 20249.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaScalaJava
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateString, Number, Booleanyesyes infosupports customizable data types and automatic typingyesyes
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 infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsSolr Parallel SQL InterfaceSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesPython.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java pluginsnono
Triggersyesyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and (since PostgreSQL 11) by hashShardingyes, utilizing Spark CoreSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoAtomic updates per row, document, or graph entity
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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