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DBMS > Hypertable vs. IRONdb vs. Sphinx vs. Vitess

System Properties Comparison Hypertable vs. IRONdb vs. Sphinx vs. Vitess

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparisonVitess  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databasesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelWide column storeTime Series DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.98
Rank#56  Overall
#5  Search engines
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/sphinxsearch.comvitess.io
Technical documentationdocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docsvitess.io/­docs
DeveloperHypertable Inc.Circonus LLC.Sphinx Technologies Inc.The Linux Foundation, PlanetScale
Initial release2009201720012013
Current release0.9.8.11, March 2016V0.10.20, January 20183.5.1, February 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C++Go
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsnoyes
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.no
Secondary indexesrestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)yes infowith proprietary extensions
APIs and other access methodsC++ API
Thrift
HTTP APIProprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes, in Luanoyes infoproprietary syntax
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelconfigurable replication factor, datacenter awarenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnononoUsers with fine-grained authorization concept infono user groups or roles

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More resources
HypertableIRONdbSphinxVitess
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