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DBMS > BigchainDB vs. InterSystems Caché vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  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 processing
Primary database modelDocument storeKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.intersystems.com/­products/­cachespark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperInterSystemsApache Software Foundation
Initial release201619972014
Current release2018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonScala
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freedepending on used data modelyes
Typing infopredefined data types such as float or datenoyesyes
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.noyesno
Secondary indexesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
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
Server-side scripts infoStored proceduresyesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
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.yesno
User concepts infoAccess controlyesAccess rights for users, groups and rolesno

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More resources
BigchainDBInterSystems CachéSpark SQL
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