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DBMS > Microsoft Azure Cosmos DB vs. Spark SQL vs. Yanza

System Properties Comparison Microsoft Azure Cosmos DB vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
DescriptionGlobally distributed, horizontally scalable, multi-model database serviceSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score40.29
Rank#26  Overall
#3  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.00
Rank#353  Overall
#34  Time Series DBMS
Websiteazure.microsoft.com/­services/­cosmos-dbspark.apache.org/­sqlyanza.com
Technical documentationdocs.microsoft.com/­azure/­cosmos-dbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftApache Software FoundationYanza
Initial release201420142015
Current release3.1.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemshostedLinux
OS X
Windows
Windows
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoJSON typesyesno
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.nono
Secondary indexesyes infoAll properties auto-indexed by defaultnono
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
ODBC
HTTP API
Supported programming languages.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresJavaScriptnono
TriggersJavaScriptnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud servicenonenone
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 systemBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-item ACID transactions with snapshot isolation within a partitionnono
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.no
User concepts infoAccess controlAccess rights can be defined down to the item levelnono

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More resources
Microsoft Azure Cosmos DB infoformer name was Azure DocumentDBSpark SQLYanza
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