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DBMS > Apache Impala vs. Apache Kylin vs. Databricks vs. Tkrzw

System Properties Comparison Apache Impala vs. Apache Kylin vs. Databricks vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonDatabricks  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackThe 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.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteimpala.apache.orgkylin.apache.orgwww.databricks.comdbmx.net/­tkrzw
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsdocs.databricks.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncDatabricksMikio Hirabayashi
Initial release2013201520132020
Current release4.1.0, June 20223.1.0, July 20200.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxLinuxhostedLinux
macOS
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesno
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.nonoyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)with Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.nononoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno
More information provided by the system vendor
Apache ImpalaApache KylinDatabricksTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaApache KylinDatabricksTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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