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DBMS > FatDB vs. Spark SQL vs. TimescaleDB vs. TypeDB

System Properties Comparison FatDB vs. Spark SQL vs. TimescaleDB vs. TypeDB

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTypeDB infoformerly named Grakn  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 time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.65
Rank#234  Overall
#20  Graph DBMS
#107  Relational DBMS
Websitespark.apache.org/­sqlwww.timescale.comtypedb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comtypedb.com/­docs
DeveloperFatCloudApache Software FoundationTimescaleVaticle
Initial release2012201420172016
Current release3.5.0 ( 2.13), September 20232.13.0, November 20232.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaCJava
Server operating systemsWindowsLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.noyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntaxno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesC#Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersyes infovia applicationsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributesSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standardyes infoat REST API level; other APIs in progress
More information provided by the system vendor
FatDBSpark SQLTimescaleDBTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
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More resources
FatDBSpark SQLTimescaleDBTypeDB infoformerly named Grakn
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