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

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

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsNewSQL 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 Cabinet
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.bigchaindb.comwww.sequoiadb.comspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationbigchaindb.readthedocs.io/­en/­latestwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSequoiadb Ltd.Apache Software FoundationMikio Hirabayashi
Initial release2016201320142020
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonC++ScalaC++
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes infooid, date, timestamp, binary, regexyesno
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 indexesyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsCLI Client
RESTful HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresJavaScriptnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controlyessimple password-based access controlnono

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More resources
BigchainDBSequoiadbSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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