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DBMS > Apache Druid vs. Apache Pinot vs. Microsoft Azure AI Search vs. Vertica

System Properties Comparison Apache Druid vs. Apache Pinot vs. Microsoft Azure AI Search vs. Vertica

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Pinot  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencySearch-as-a-service for web and mobile app developmentCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsVector DBMSSpatial DBMS
Time Series 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
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedruid.apache.orgpinot.apache.orgazure.microsoft.com/­en-us/­services/­searchwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.pinot.apache.orglearn.microsoft.com/­en-us/­azure/­searchvertica.com/­documentation
DeveloperApache Software Foundation and contributorsApache Software Foundation and contributorsMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201520152005
Current release29.0.1, April 20241.0.0, September 2023V112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Unix
All OS with a Java JDK11 or higherhostedLinux
Data schemeyes infoschema-less columns are supportedyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.nonono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingSQL-like query languagenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCRESTful HTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
Python
C#
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioningSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud serviceMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes infousing Azure authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidApache PinotMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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Apache DruidApache PinotMicrosoft Azure AI SearchVertica infoOpenText™ Vertica™
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