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DBMS > FatDB vs. Interbase vs. TimescaleDB vs. Vertica

System Properties Comparison FatDB vs. Interbase vs. TimescaleDB vs. Vertica

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInterbase  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Light-weight proven RDBMS infooriginally from BorlandA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.78
Rank#77  Overall
#41  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.embarcadero.com/­products/­interbasewww.timescale.comwww.vertica.com
Technical documentationdocs.embarcadero.com/­products/­interbasedocs.timescale.comvertica.com/­documentation
DeveloperFatCloudEmbarcaderoTimescaleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012198420172005
Current releaseInterBase 2020, December 20192.15.0, May 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#CCC++
Server operating systemsWindowsAndroid
iOS
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.no infoexport as XML data possibleyesno
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryesyes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyes infoInterbase procedure and trigger languageuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInterbase Change ViewsSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes
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.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
FatDBInterbaseTimescaleDBVertica infoOpenText™ Vertica™
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