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

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

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFatDB  Xexclude from comparisonInterbase  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 distributed reliable key-value storeA .NET NoSQL DBMS that can integrate with and extend SQL Server.Light-weight proven RDBMS infooriginally from BorlandSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.embarcadero.com/­products/­interbasespark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.embarcadero.com/­products/­interbasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudEmbarcaderoApache Software Foundation
Initial release201219842014
Current release3.4, August 2019InterBase 2020, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen 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 languageGoC#CScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
WindowsAndroid
iOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 infoexport as XML data possibleno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServeryesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
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#.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes infoInterbase procedure and trigger languageno
Triggersyes, watching key changesyes infovia applicationsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, 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 factorInterbase Change Viewsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyes
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.noyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardno

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More resources
etcdFatDBInterbaseSpark SQL
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