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DBMS > Databend vs. Interbase vs. Spark SQL

System Properties Comparison Databend vs. Interbase vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonInterbase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityLight-weight proven RDBMS infooriginally from BorlandSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.embarcadero.com/­products/­interbasespark.apache.org/­sql
Technical documentationdocs.databend.comdocs.embarcadero.com/­products/­interbasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsEmbarcaderoApache Software Foundation
Initial release202119842014
Current release1.0.59, April 2023InterBase 2020, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustCScala
Server operating systemshosted
Linux
macOS
Android
iOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono infoexport as XML data possibleno
Secondary indexesnoyesno
SQL infoSupport of SQLyesyesSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoInterbase procedure and trigger languageno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInterbase Change Viewsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardno

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More resources
DatabendInterbaseSpark SQL
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