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DBMS > Hypertable vs. SiriDB vs. Spark SQL vs. Sphinx

System Properties Comparison Hypertable vs. SiriDB vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopOpen 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 modelWide column storeTime Series DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitesiridb.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperHypertable Inc.CesbitApache Software FoundationSphinx Technologies Inc.
Initial release2009201720142001
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license 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 systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes 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.nono
Secondary indexesrestricted infoonly exact value or prefix value scansyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsC++ API
Thrift
HTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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 nodesShardingShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.yesno
User concepts infoAccess controlnosimple rights management via user accountsnono

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More resources
HypertableSiriDBSpark SQLSphinx
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