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DBMS > FatDB vs. Graphite vs. Hive vs. Spark SQL

System Properties Comparison FatDB vs. Graphite vs. Hive vs. Spark SQL

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGraphite  Xexclude from comparisonHive  Xexclude from comparisonSpark SQL  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.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called Whisperdata warehouse software for querying and managing large distributed datasets, built on HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­graphite-project/­graphite-webhive.apache.orgspark.apache.org/­sql
Technical documentationgraphite.readthedocs.iocwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudChris DavisApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release2012200620122014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0
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#PythonJavaScala
Server operating systemsWindowsLinux
Unix
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
Sockets
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC#JavaScript (Node.js)
Python
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnoyes infouser defined functions and integration of map-reduceno
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
noneEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnoAccess rights for users, groups and rolesno

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More resources
FatDBGraphiteHiveSpark SQL
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