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

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

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonReductStore  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 assetsDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark 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 storeTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.bigchaindb.comgithub.com/­reductstore
www.reduct.store
spark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationbigchaindb.readthedocs.io/­en/­latestwww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperReductStore LLCApache Software FoundationMikio Hirabayashi
Initial release2016202320142020
Current release1.9, March 20243.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoBusiness Source License 1.1Open 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++, RustScalaC++
Server operating systemsLinuxDocker
Linux
macOS
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesno
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 indexesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsCLI Client
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlyesnono

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More resources
BigchainDBReductStoreSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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