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DBMS > Apache Impala vs. FeatureBase vs. Riak KV vs. Sphinx

System Properties Comparison Apache Impala vs. FeatureBase vs. Riak KV vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFeatureBase  Xexclude from comparisonRiak KV  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Distributed, fault tolerant key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgwww.featurebase.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.featurebase.comwww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMolecula and Pilosa Open Source ContributorsOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release2013201720092001
Current release4.1.0, June 20222022, May 20223.2.0, December 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoErlangC++
Server operating systemsLinuxLinux
macOS
Linux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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 indexesyesnorestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL queriesnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
HTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCJava
Python
C 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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceErlangno
Triggersnonoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 Kerberosyes, using Riak Securityno

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More resources
Apache ImpalaFeatureBaseRiak KVSphinx
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