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DBMS > Microsoft Azure Cosmos DB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Microsoft Azure Cosmos DB vs. Sadas Engine vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGlobally distributed, horizontally scalable, multi-model database serviceSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score40.98
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.00
Rank#360  Overall
#156  Relational DBMS
Score23.12
Rank#35  Overall
#21  Relational DBMS
Websiteazure.microsoft.com/­services/­cosmos-dbwww.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­azure/­cosmos-dbwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftSADAS s.r.l.Apache Software Foundation
Initial release201420062014
Current release8.03.2.0, October 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedAIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoJSON typesyesyes
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 defaultyesno
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statements
APIs and other access methodsDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languages.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresJavaScriptnono
TriggersJavaScriptnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, utilizing Spark Core
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-item ACID transactions with snapshot isolation within a partitionno
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.yes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights can be defined down to the item levelAccess rights for users, groups and roles according to SQL-standardno

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More resources
Microsoft Azure Cosmos DB infoformer name was Azure DocumentDBSadas EngineSpark SQL
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