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DBMS > Apache Impala vs. EventStoreDB vs. Linter

System Properties Comparison Apache Impala vs. EventStoreDB vs. Linter

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEventStoreDB  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopIndustrial-strength, open-source database solution built from the ground up for event sourcing.RDBMS for high security requirements
Primary database modelRelational DBMSEvent StoreRelational 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
Score1.10
Rank#179  Overall
#1  Event Stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websiteimpala.apache.orgwww.eventstore.comlinter.ru
Technical documentationimpala.apache.org/­impala-docs.htmldevelopers.eventstore.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEvent Store Limitedrelex.ru
Initial release201320121990
Current release4.1.0, June 202221.2, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++
Server operating systemsLinuxLinux
Windows
AIX
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 statementsyes
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-reduceyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone
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 MapReduceno
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
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.no
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 ImpalaEventStoreDBLinter
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News



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