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DBMS > Databricks vs. Microsoft Azure Cosmos DB vs. Sadas Engine

System Properties Comparison Databricks vs. Microsoft Azure Cosmos DB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSadas Engine  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 serviceSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse 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
Score0.00
Rank#392  Overall
#158  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­services/­cosmos-dbwww.sadasengine.com
Technical documentationdocs.databricks.comlearn.microsoft.com/­azure/­cosmos-dbwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperDatabricksMicrosoftSADAS s.r.l.
Initial release201320142006
Current release8.0
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedAIX
Linux
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.yesno
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
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesJavaScriptno
TriggersJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud servicenone
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 partition
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 infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights can be defined down to the item levelAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSadas Engine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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More resources
DatabricksMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSadas Engine
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FT & Databricks Partner to Modernise Insurers' AI Data Systems
12 December 2024, FinTech Magazine

Kleiner Perkins, Founders Fund, SoftBank to Invest in Databricks’ $7 Billion Fundraising
12 December 2024, The Information

They Teamed Up On Databricks And Perplexity. Now They're Launching Their Own $150 Million Fund
10 December 2024, Forbes

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