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

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

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonetcd  Xexclude from comparisonFatDB  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 distributed reliable key-value storeA .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSKey-value storeDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.ioetcd.io
github.com/­etcd-io/­etcd
spark.apache.org/­sql
Technical documentationdocs.atoti.ioetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamFatCloudApache Software Foundation
Initial release20122014
Current release3.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2.0commercialOpen 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 languageJavaGoC#Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
WindowsLinux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes
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 indexesnoyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)nono infoVia inetgration in SQL ServerSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnoyes infovia applicationsno
Triggersyes, watching key changesyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate 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.yesnono
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsno

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More resources
atotietcdFatDBSpark SQL
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