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DBMS > FatDB vs. Interbase vs. Spark SQL vs. TimescaleDB vs. Titan

System Properties Comparison FatDB vs. Interbase vs. Spark SQL vs. TimescaleDB vs. Titan

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInterbase  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTitan  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionA .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 processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSTime Series DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.embarcadero.com/­products/­interbasespark.apache.org/­sqlwww.timescale.comgithub.com/­thinkaurelius/­titan
Technical documentationdocs.embarcadero.com/­products/­interbasespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperFatCloudEmbarcaderoApache Software FoundationTimescaleAurelius, owned by DataStax
Initial release20121984201420172012
Current releaseInterBase 2020, December 20193.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#CScalaCJava
Server operating systemsWindowsAndroid
iOS
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.no infoexport as XML data possiblenoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-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
ADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes infoInterbase procedure and trigger languagenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyes infovia applicationsyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributesyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInterbase Change ViewsnoneSource-replica replication with hot standby and reads on replicas infoyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
FatDBInterbaseSpark SQLTimescaleDBTitan
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