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DBMS > Apache Impala vs. mSQL vs. Spark SQL vs. Transwarp StellarDB

System Properties Comparison Apache Impala vs. mSQL vs. Spark SQL vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopmSQL (Mini SQL) is a simple and lightweight RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingA distributed graph DBMS built for enterprise-level graph applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#361  Overall
#38  Graph DBMS
Websiteimpala.apache.orghughestech.com.au/­products/­msqlspark.apache.org/­sqlwww.transwarp.cn/­en/­product/­stellardb
Technical documentationimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHughes TechnologiesApache Software FoundationTranswarp
Initial release201319942014
Current release4.1.0, June 20224.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree licenses can be providedOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CScala
Server operating systemsLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Windows
Data schemeyesyesyes
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 statementsA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
OpenCypher
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Delphi
Java
Perl
PHP
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistencynone
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
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 Kerberosnonoyes

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More resources
Apache ImpalamSQL infoMini SQLSpark SQLTranswarp StellarDB
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