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DBMS > Apache Impala vs. EsgynDB vs. Hyprcubd vs. Kinetica

System Properties Comparison Apache Impala vs. EsgynDB vs. Hyprcubd vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonKinetica  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionServerless Time Series DBMSFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cnhyprcubd.com (offline)www.kinetica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynHyprcubd, Inc.Kinetica
Initial release201320152012
Current release4.1.0, June 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaGoC, C++
Server operating systemsLinuxLinuxhostedLinux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyes
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-like DML and DDL statementsyesSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
gRPC (https)JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresnouser defined functions
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
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 infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardtoken accessAccess rights for users and roles on table level

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More resources
Apache ImpalaEsgynDBHyprcubdKinetica
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