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DBMS > DuckDB vs. Sequoiadb vs. Spark SQL vs. Yaacomo

System Properties Comparison DuckDB vs. Sequoiadb vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteduckdb.orgwww.sequoiadb.comspark.apache.org/­sqlyaacomo.com
Technical documentationduckdb.org/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSequoiadb Ltd.Apache Software FoundationQ2WEB GmbH
Initial release2018201320142009
Current release0.10, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Scala
Server operating systemsserver-lessLinuxLinux
OS X
Windows
Android
Linux
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infooid, date, timestamp, binary, regexyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
proprietary protocol using JSONJDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJavaScriptno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDDocument is locked during a transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesnonoyes
User concepts infoAccess controlnosimple password-based access controlnofine grained access rights according to SQL-standard

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More resources
DuckDBSequoiadbSpark SQLYaacomo
Recent citations in the news

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

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