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DBMS > BaseX vs. FatDB vs. NSDb vs. Spark SQL vs. Teradata Aster

System Properties Comparison BaseX vs. FatDB vs. NSDb vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameBaseX  Xexclude from comparisonFatDB  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelNative XML DBMSDocument store
Key-value store
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebasex.orgnsdb.iospark.apache.org/­sql
Technical documentationdocs.basex.orgnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBaseX GmbHFatCloudApache Software FoundationTeradata
Initial release20072012201720142005
Current release10.7, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Java, ScalaScala
Server operating systemsLinux
OS X
Windows
WindowsLinux
macOS
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateno infoXQuery supports typesyesyes: int, bigint, decimal, stringyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC
HTTP REST
WebSocket
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C#Java
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyes infovia applicationsnonoR packages
Triggersyes infovia eventsyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factornoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datamultiple readers, single writernononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUsers with fine-grained authorization concept on 4 levelsno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standard

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More resources
BaseXFatDBNSDbSpark SQLTeradata Aster
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