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DBMS > FatDB vs. InfluxDB vs. Spark SQL vs. Sphinx vs. YottaDB

System Properties Comparison FatDB vs. InfluxDB vs. Spark SQL vs. Sphinx vs. YottaDB

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonYottaDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.DBMS for storing time series, events and metricsSpark 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 databasesA fast and solid embedded Key-value store
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSSearch engineKey-value store
Secondary database modelsSpatial DBMS infowith GEO packageRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.20
Rank#317  Overall
#47  Key-value stores
Websitewww.influxdata.com/­products/­influxdb-overviewspark.apache.org/­sqlsphinxsearch.comyottadb.com
Technical documentationdocs.influxdata.com/­influxdbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docsyottadb.com/­resources/­documentation
DeveloperFatCloudApache Software FoundationSphinx Technologies Inc.YottaDB, LLC
Initial release20122013201420012001
Current release2.7.6, April 20243.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#GoScalaC++C
Server operating systemsWindowsLinux
OS X infothrough Homebrew
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyesnono
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 indexesyesnonoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (SphinxQL)by using the Octo plugin
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
JSON over UDP
JDBC
ODBC
Proprietary protocolPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC#.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes infovia applicationsnonono
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyyes, 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 factorselectable replication factor infoin enterprise version onlynonenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononooptimistic locking
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.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage enginenoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationssimple rights management via user accountsnonoUsers and groups based on OS-security mechanisms
More information provided by the system vendor
FatDBInfluxDBSpark SQLSphinxYottaDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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