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DBMS > Apache Pinot vs. Datomic vs. EsgynDB vs. Hive

System Properties Comparison Apache Pinot vs. Datomic vs. EsgynDB vs. Hive

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatomic  Xexclude from comparisonEsgynDB  Xexclude from comparisonHive  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodiondata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitepinot.apache.orgwww.datomic.comwww.esgyn.cnhive.apache.org
Technical documentationdocs.pinot.apache.orgdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation and contributorsCognitectEsgynApache Software Foundation infoinitially developed by Facebook
Initial release2015201220152012
Current release1.0.0, September 20231.0.6735, June 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC++, JavaJava
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VMLinuxAll OS with a Java VM
Data schemeyesyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesSQL-like DML and DDL statements
APIs and other access methodsJDBCRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
ODBC
Thrift
Supported programming languagesGo
Java
Python
Clojure
Java
All languages supporting JDBC/ODBC/ADO.NetC++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJava Stored Proceduresyes infouser defined functions and integration of map-reduce
TriggersBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication between multi datacentersselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
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 persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles

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More resources
Apache PinotDatomicEsgynDBHive
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