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DBMS > Apache Impala vs. Tkrzw vs. Yaacomo

System Properties Comparison Apache Impala vs. Tkrzw vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score0.05
Rank#380  Overall
#59  Key-value stores
Websiteimpala.apache.orgdbmx.net/­tkrzwyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMikio HirabayashiQ2WEB GmbH
Initial release201320202009
Current release4.1.0, June 20220.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxLinux
macOS
Android
Linux
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceno
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
Recent citations in the news

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

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

How different SQL-on-Hadoop engines satisfy BI workloads
24 February 2016, CIO

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

provided by Google News



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