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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInterbase  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  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 DBMS designed for efficient storage of vector data and vector similarity searchesSpark 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 PostgreSQL
Primary database modelDocument store
Key-value store
Relational DBMSVector DBMSRelational DBMSTime Series 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
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.embarcadero.com/­products/­interbasemilvus.iospark.apache.org/­sqlwww.timescale.com
Technical documentationdocs.embarcadero.com/­products/­interbasemilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperFatCloudEmbarcaderoApache Software FoundationTimescale
Initial release20121984201920142017
Current releaseInterBase 2020, December 20192.3.4, January 20243.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC#CC++, GoScalaC
Server operating systemsWindowsAndroid
iOS
Linux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 possiblenonoyes
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesnoSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infovia applicationsyes infoInterbase procedure and trigger languagenonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infovia applicationsyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInterbase Change ViewsnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardRole based access control and fine grained access rightsnofine grained access rights according to SQL-standard
More information provided by the system vendor
FatDBInterbaseMilvusSpark SQLTimescaleDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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FatDBInterbaseMilvusSpark SQLTimescaleDB
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