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DBMS > Microsoft Azure Table Storage vs. Riak TS vs. Spark SQL vs. Sphinx

System Properties Comparison Microsoft Azure Table Storage vs. Riak TS vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelWide column storeTime Series DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.28
Rank#307  Overall
#27  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlsphinxsearch.com
Technical documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperMicrosoftOpen Source, formerly Basho TechnologiesApache Software FoundationSphinx Technologies Inc.
Initial release2012201520142001
Current release3.0.0, September 20223.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangScalaC++
Server operating systemshostedLinux
OS X
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesno
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 indexesnorestrictednoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, limitedSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIHTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoErlangnono
Triggersnoyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between datasets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesnonono

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More resources
Microsoft Azure Table StorageRiak TSSpark SQLSphinx
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