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DBMS > Databricks vs. IBM Cloudant vs. Spark SQL

System Properties Comparison Databricks vs. IBM Cloudant vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Database as a Service offering based on Apache CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score2.73
Rank#108  Overall
#20  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­cloudantspark.apache.org/­sql
Technical documentationdocs.databricks.comcloud.ibm.com/­docs/­Cloudantspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Apache Software Foundation
Initial release201320102014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangScala
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyes
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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesPython
R
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions (Map-Reduce) in JavaScriptno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
DatabricksIBM CloudantSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksIBM CloudantSpark SQL
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