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DBMS > Cachelot.io vs. Hypertable vs. IRONdb vs. Sphinx vs. TimescaleDB

System Properties Comparison Cachelot.io vs. Hypertable vs. IRONdb vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonHypertable  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  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.
DescriptionIn-memory caching systemAn 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 databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeWide column storeTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitecachelot.iowww.circonus.com/solutions/time-series-database/sphinxsearch.comwww.timescale.com
Technical documentationdocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docsdocs.timescale.com
DeveloperHypertable Inc.Circonus LLC.Sphinx Technologies Inc.Timescale
Initial release20152009201720012017
Current release0.9.8.11, March 2016V0.10.20, January 20183.5.1, February 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C and C++C++C
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoyes infotext, numeric, histogramsnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesnorestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsMemcached protocolC++ API
Thrift
HTTP APIProprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C++
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes, in Luanouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingAutomatic, metric affinity per nodeSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor on file system levelconfigurable replication factor, datacenter awarenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentnoyesyesyes 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.nonono
User concepts infoAccess controlnonononofine grained access rights according to SQL-standard

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More resources
Cachelot.ioHypertableIRONdbSphinxTimescaleDB
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