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

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

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFatDB  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.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A .NET NoSQL DBMS that can integrate with and extend SQL Server.data 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 modelObject oriented DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iohive.apache.orgspark.apache.org/­sql
Technical documentationdocs.atoti.iocwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamFatCloudApache Software Foundation infoinitially developed by FacebookApache Software Foundation
Initial release201220122014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen 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 languageJavaC#JavaScala
Server operating systemsWindowsAll OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)no infoVia inetgration in SQL ServerSQL-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
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC#C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infovia applicationsyes infouser defined functions and integration of map-reduceno
Triggersyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesno

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atotiFatDBHiveSpark SQL
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