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DBMS > Databricks vs. Microsoft Azure Data Explorer vs. Sequoiadb

System Properties Comparison Databricks vs. Microsoft Azure Data Explorer vs. Sequoiadb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSequoiadb  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.Fully managed big data interactive analytics platformNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Relational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score83.29
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.57
Rank#81  Overall
#44  Relational DBMS
Score0.40
Rank#269  Overall
#42  Document stores
#125  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­services/­data-explorerwww.sequoiadb.com
Technical documentationdocs.databricks.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksMicrosoftSequoiadb Ltd.
Initial release201320192013
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2
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 systemshostedhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infooid, date, timestamp, binary, regex
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.yesyesno
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesYes, possible languages: KQL, Python, RJavaScript
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoDocument is locked during a transaction
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.nonono
User concepts infoAccess controlAzure Active Directory Authenticationsimple password-based access control
More information provided by the system vendor
DatabricksMicrosoft Azure Data ExplorerSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksMicrosoft Azure Data ExplorerSequoiadb
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