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DBMS > Apache Impala vs. Pinecone vs. Solr vs. Spark SQL

System Properties Comparison Apache Impala vs. Pinecone vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPinecone  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA managed, cloud-native vector databaseA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSVector DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.pinecone.iosolr.apache.orgspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.pinecone.io/­docs/­overviewsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPinecone Systems, IncApache Software FoundationApache Software Foundation
Initial release2013201920062014
Current release4.1.0, June 20229.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScala
Server operating systemsLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesString, Number, Booleanyes infosupports customizable data types and automatic typingyes
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 indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava pluginsno
Triggersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingno
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesno

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Apache ImpalaPineconeSolrSpark SQL
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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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27 October 2017, KDnuggets

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11 June 2024, PR Newswire

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14 June 2024, Yahoo Movies UK

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

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12 June 2024, MarkTechPost

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21 November 2023, Equity.Guru

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