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DBMS > Apache Impala vs. atoti vs. Linter

System Properties Comparison Apache Impala vs. atoti vs. Linter

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonatoti  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.RDBMS for high security requirements
Primary database modelRelational DBMSObject oriented DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websiteimpala.apache.orgatoti.iolinter.ru
Technical documentationimpala.apache.org/­impala-docs.htmldocs.atoti.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaActiveViamrelex.ru
Initial release20131990
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree versions availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++
Server operating systemsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsMultidimensional Expressions (MDX)yes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePythonyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard

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More resources
Apache ImpalaatotiLinter
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