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DBMS > Apache Impala vs. Databricks vs. mSQL vs. Riak KV

System Properties Comparison Apache Impala vs. Databricks vs. mSQL vs. Riak KV

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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.mSQL (Mini SQL) is a simple and lightweight RDBMSDistributed, fault tolerant key-value store
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteimpala.apache.orgwww.databricks.comhughestech.com.au/­products/­msql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksHughes TechnologiesOpenSource, formerly Basho Technologies
Initial release2013201319942009
Current release4.1.0, June 20224.4, October 20213.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree licenses can be providedOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CErlang
Server operating systemsLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-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.noyesnono
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C++
Delphi
Java
Perl
PHP
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoErlang
Triggersnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be stored
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnoyes, using Riak Security
More information provided by the system vendor
Apache ImpalaDatabricksmSQL infoMini SQLRiak KV
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksmSQL infoMini SQLRiak KV
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