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DBMS > Apache Impala vs. Tkrzw vs. Vitess vs. Yaacomo

System Properties Comparison Apache Impala vs. Tkrzw vs. Vitess 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 comparisonVitess  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 CabinetScalable, distributed, cloud-native DBMS, extending MySQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteimpala.apache.orgdbmx.net/­tkrzwvitess.ioyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMikio HirabayashiThe Linux Foundation, PlanetScaleQ2WEB GmbH
Initial release2013202020132009
Current release4.1.0, June 20220.9.3, August 202015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Go
Server operating systemsLinuxLinux
macOS
Docker
Linux
macOS
Android
Linux
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoproprietary syntax
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.noyes infousing specific database classesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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27 October 2017, KDnuggets

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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

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18 May 2021, The Register

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13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

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