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DBMS > Apache Pinot vs. Databricks vs. EsgynDB vs. Microsoft Azure AI Search

System Properties Comparison Apache Pinot vs. Databricks vs. EsgynDB vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitepinot.apache.orgwww.databricks.comwww.esgyn.cnazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.pinot.apache.orgdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation and contributorsDatabricksEsgynMicrosoft
Initial release2015201320152015
Current release1.0.0, September 2023V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java
Server operating systemsAll OS with a Java JDK11 or higherhostedLinuxhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLyesno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
Python
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 controlfine grained access rights according to SQL-standardyes infousing Azure authentication
More information provided by the system vendor
Apache PinotDatabricksEsgynDBMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PinotDatabricksEsgynDBMicrosoft Azure AI Search
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