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DBMS > Apache Druid vs. Pinecone vs. Spark SQL vs. Typesense

System Properties Comparison Apache Druid vs. Pinecone vs. Spark SQL vs. Typesense

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMS
Time Series DBMS
Vector DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.79
Rank#210  Overall
#14  Search engines
Websitedruid.apache.orgwww.pinecone.iospark.apache.org/­sqltypesense.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypesense.org/­docs
DeveloperApache Software Foundation and contributorsPinecone Systems, IncApache Software Foundation
Initial release2012201920142015
Current release29.0.1, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesString, Number, Booleanyesyes
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
PythonJava
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresnonono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno

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More resources
Apache DruidPineconeSpark SQLTypesense
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