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DBMS > Databend vs. EJDB vs. Spark SQL

System Properties Comparison Databend vs. EJDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonEJDB  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 complexityEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
github.com/­Softmotions/­ejdbspark.apache.org/­sql
Technical documentationdocs.databend.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsSoftmotionsApache Software Foundation
Initial release202120122014
Current release1.0.59, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2Open 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
server-lessLinux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes
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
Secondary indexesnonono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
in-process shared libraryJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenone
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 infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes
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.no
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnono

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More resources
DatabendEJDBSpark SQL
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