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DBMS > Apache Impala vs. Kinetica vs. LeanXcale vs. SiteWhere

System Properties Comparison Apache Impala vs. Kinetica vs. LeanXcale vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteimpala.apache.orgwww.kinetica.comwww.leanxcale.comgithub.com/­sitewhere/­sitewhere
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.comsitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKineticaLeanXcaleSiteWhere
Initial release2013201220152010
Current release4.1.0, June 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++Java
Server operating systemsLinuxLinuxLinux
OS X
Windows
Data schemeyesyesyespredefined scheme
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infothrough Apache Derbyno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
C
Java
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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.noyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and roles on table levelUsers with fine-grained authorization concept

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More resources
Apache ImpalaKineticaLeanXcaleSiteWhere
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