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

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

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Editorial information provided by DB-Engines
NameSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.sequoiadb.comspark.apache.org/­sqldbmx.net/­tkrzwyaacomo.com
Technical documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSequoiadb Ltd.Apache Software FoundationMikio HirabayashiQ2WEB GmbH
Initial release2013201420202009
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS
Android
Linux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes infooid, date, timestamp, binary, regexyesnoyes
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoyes
APIs and other access methodsproprietary protocol using JSONJDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C++
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresJavaScriptnono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataDocument is locked during a transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes infousing specific database classesyes
User concepts infoAccess controlsimple password-based access controlnonofine grained access rights according to SQL-standard

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More resources
SequoiadbSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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