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DBMS > FatDB vs. IRONdb vs. Kyligence Enterprise vs. Solr vs. Yaacomo

System Properties Comparison FatDB vs. IRONdb vs. Kyligence Enterprise vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIRONdb  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA distributed analytics engine for big data, built on top of Apache KylinA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#354  Overall
#33  Time Series DBMS
Score0.24
Rank#282  Overall
#132  Relational DBMS
Score57.26
Rank#20  Overall
#3  Search engines
Score0.00
Rank#354  Overall
#152  Relational DBMS
Websitewww.circonus.com/­solutions/­time-series-databasekyligence.io/­kyligence-enterpriselucene.apache.org/­solryaacomo.com
Technical documentationdocs.circonus.com/­irondblucene.apache.org/­solr/­resources.html
DeveloperFatCloudCirconus LLC.Kyligence, Inc.Apache Software FoundationQ2WEB GmbH
Initial release20122017201620062009
Current releaseV0.10.20, January 20189.0.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C and C++JavaJava
Server operating systemsWindowsLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (Circonus Analytics Query Language: CAQL)ANSI SQL for queries (using Apache Calcite)Solr Parallel SQL Interfaceyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP APIJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC#.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, in LuaJava plugins
Triggersyes infovia applicationsnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorconfigurable replication factor, datacenter awareyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency per node, eventual consistency across nodesImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnoyesfine grained access rights according to SQL-standard

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More resources
FatDBIRONdbKyligence EnterpriseSolrYaacomo
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