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DBMS > Databricks vs. Microsoft Azure Table Storage

System Properties Comparison Databricks vs. Microsoft Azure Table Storage

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Our visitors often compare Databricks and Microsoft Azure Table Storage with Microsoft Azure Cosmos DB, Microsoft SQL Server and Microsoft Azure SQL Database.

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Table Storage  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.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score2.64
Rank#94  Overall
#7  Wide column stores
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.com
DeveloperDatabricksMicrosoft
Initial release20132012
License infoCommercial or Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyes
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 indexesyesno
SQL infoSupport of SQLwith Databricks SQLno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signatures

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More resources
DatabricksMicrosoft Azure Table Storage
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