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DBMS > Apache Druid vs. Coveo vs. Spark SQL vs. SpatiaLite

System Properties Comparison Apache Druid vs. Coveo vs. Spark SQL vs. SpatiaLite

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCoveo  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentSpark SQL is a component on top of 'Spark Core' for structured data processingSpatial extension of SQLite
Primary database modelRelational DBMS
Time Series DBMS
Search engineRelational DBMSSpatial DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.63
Rank#146  Overall
#3  Spatial DBMS
Websitedruid.apache.orgwww.coveo.comspark.apache.org/­sqlwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.coveo.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software Foundation and contributorsCoveoApache Software FoundationAlessandro Furieri
Initial release2012201220142008
Current release29.0.1, April 20243.5.0 ( 2.13), September 20235.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
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
server-less
Data schemeyes infoschema-less columns are supportedhybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
JavaScript
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemgranular access controls, API key management, content filtersnono

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More resources
Apache DruidCoveoSpark SQLSpatiaLite
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