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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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.
DescriptionA .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 resource-optimized, high-performance, universally applicable RDBMSA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.20
Rank#327  Overall
#144  Relational DBMS
Score0.16
Rank#336  Overall
#48  Document stores
Websitespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlwww.xtdb.com/­docs
DeveloperFatCloudApache Software FoundationTransaction Software GmbHJuxt Ltd.
Initial release2012201419872019
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 20221.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree development licenseOpen 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 languageC#ScalaC and C++Clojure
Server operating systemsWindowsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, 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 indexesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyeslimited SQL, making use of Apache Calcite
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP REST
JDBC
Supported programming languagesC#Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresyes infovia applicationsnoyesno
Triggersyes infovia applicationsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID
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 controlno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standard

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More resources
FatDBSpark SQLTransbaseXTDB infoformerly named Crux
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