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DBMS > Badger vs. FatDB vs. Spark SQL vs. XTDB

System Properties Comparison Badger vs. FatDB vs. Spark SQL vs. XTDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processingA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value storeDocument store
Key-value store
Relational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitegithub.com/­dgraph-io/­badgerspark.apache.org/­sqlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.xtdb.com/­docs
DeveloperDGraph LabsFatCloudApache Software FoundationJuxt Ltd.
Initial release2017201220142019
Current release3.5.0 ( 2.13), September 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC#ScalaClojure
Server operating systemsBSD
Linux
OS X
Solaris
Windows
WindowsLinux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes, extensible-data-notation format
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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statementslimited SQL, making use of Apache Calcite
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
HTTP REST
JDBC
Supported programming languagesGoC#Java
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresnoyes infovia applicationsnono
Triggersnoyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factornoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsno

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More resources
BadgerFatDBSpark SQLXTDB infoformerly named Crux
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