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DBMS > BigchainDB vs. InterSystems Caché vs. Spark SQL vs. Tkrzw

System Properties Comparison BigchainDB vs. InterSystems Caché vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA multi-model DBMS and application serverSpark 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 storeKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.bigchaindb.comwww.intersystems.com/­products/­cachespark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperInterSystemsApache Software FoundationMikio Hirabayashi
Initial release2016199720142020
Current release2018.1.4, May 20203.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen 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 languagePythonScalaC++
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freedepending on used data modelyesschema-free
Typing infopredefined data types such as float or datenoyesyesno
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.noyesnono
Secondary indexesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsCLI Client
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Java
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, 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 systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
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.yesnoyes infousing specific database classes
User concepts infoAccess controlyesAccess rights for users, groups and rolesnono

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More resources
BigchainDBInterSystems CachéSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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