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DBMS > Apache Impala vs. Riak TS vs. Splunk

System Properties Comparison Apache Impala vs. Riak TS vs. Splunk

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonRiak TS  Xexclude from comparisonSplunk  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVAnalytics Platform for Big Data
Primary database modelRelational DBMSTime Series DBMSSearch engine
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
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Score88.71
Rank#14  Overall
#2  Search engines
Websiteimpala.apache.orgwww.splunk.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latestdocs.splunk.com/­Documentation/­Splunk
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOpen Source, formerly Basho TechnologiesSplunk Inc.
Initial release201320152003
Current release4.1.0, June 20223.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Sourcecommercial infoLimited free edition and free developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Erlang
Server operating systemsLinuxLinux
OS X
Linux
OS X
Solaris
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.nonoyes
Secondary indexesyesrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, limitedno infoSplunk Search Processing Language for search commands
APIs and other access methodsJDBC
ODBC
HTTP API
Native Erlang Interface
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBCC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceErlangyes
Triggersnoyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users and roles

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More resources
Apache ImpalaRiak TSSplunk
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29 July 2021, iProgrammer

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

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28 November 2017, Datanami

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24 June 2022, InfoWorld

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

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6 October 2015, The Register

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