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DBMS > Databricks vs. Microsoft Azure Cosmos DB vs. SAP SQL Anywhere

System Properties Comparison Databricks vs. Microsoft Azure Cosmos DB vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  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.Globally distributed, horizontally scalable, multi-model database serviceRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelDocument store
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score87.68
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Score23.06
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score3.18
Rank#82  Overall
#45  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­services/­cosmos-dbwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationdocs.databricks.comlearn.microsoft.com/­azure/­cosmos-dbhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperDatabricksMicrosoftSAP infoformerly Sybase
Initial release201320141992
Current release17, July 2015
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Server operating systemshostedhostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyes infoJSON typesyes
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.yesyes
Secondary indexesyesyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesJavaScriptyes, in C/C++, Java, .Net or Perl
TriggersJavaScriptyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud serviceSource-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDMulti-item ACID transactions with snapshot isolation within a partitionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes
User concepts infoAccess controlAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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