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DBMS > Databricks vs. IBM Cloudant vs. Microsoft Access vs. Splice Machine

System Properties Comparison Databricks vs. IBM Cloudant vs. Microsoft Access vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSplice Machine  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 CouchDBMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score2.85
Rank#95  Overall
#18  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­cloudantwww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.com
Technical documentationdocs.databricks.comcloud.ibm.com/­docs/­Cloudantdeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperDatabricksIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftSplice Machine
Initial release2013201019922014
Current release1902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++Java
Server operating systemshostedhostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
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.yesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesPython
R
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions (Map-Reduce) in JavaScriptyes infosince Access 2010 using the ACE-engineyes infoJava
Triggersyesyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a document possibleACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseno infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksIBM CloudantMicrosoft AccessSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksIBM CloudantMicrosoft AccessSplice Machine
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