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DBMS > Sadas Engine vs. SiriDB vs. Spark SQL vs. Sphinx

System Properties Comparison Sadas Engine vs. SiriDB vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameSadas Engine  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsOpen Source Time Series DBMSSpark 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 modelRelational DBMSTime Series DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#329  Overall
#142  Relational DBMS
Score0.01
Rank#347  Overall
#35  Time Series DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score8.03
Rank#55  Overall
#6  Search engines
Websitewww.sadasengine.comsiridb.netspark.apache.org/­sqlsphinxsearch.com
Technical documentationwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbdocs.siridb.netspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperSADAS s.r.l.Transceptor TechnologyApache Software FoundationSphinx Technologies Inc.
Initial release2006201720142001
Current release8.03.2.0, October 20213.4.1, July 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoApache 2.0Open 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++CScalaC++
Server operating systemsAIX
Linux
Windows
LinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoNumeric datayesno
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
HTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Python
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.yes infomanaged by 'Learn by Usage'yesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accountsnono

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More resources
Sadas EngineSiriDBSpark SQLSphinx
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