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DBMS > Databend vs. gStore vs. Spark SQL

System Properties Comparison Databend vs. gStore vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisongStore  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 complexityA native Graph DBMS to store and maintain very large RDF datasets.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
en.gstore.cnspark.apache.org/­sql
Technical documentationdocs.databend.comen.gstore.cn/­#/­enDocsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsApache Software Foundation
Initial release202120162014
Current release1.0.59, April 20231.2, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen 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 languageRustC++Scala
Server operating systemshosted
Linux
macOS
LinuxLinux
OS X
Windows
Data schemeyesschema-free and OWL/RDFS-schema supportyes
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.nonono
Secondary indexesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C++
Java
JavaScript (Node.js)
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesUsers, roles and permissions, Role-Based Access Control (RBAC) supportedno

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More resources
DatabendgStoreSpark SQL
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