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

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

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.The 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 platform
Primary database modelObject oriented DBMSDocument store
Relational DBMS
Relational DBMS infocolumn oriented
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
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatoti.iowww.databricks.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.atoti.iodocs.databricks.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperActiveViamDatabricksMicrosoft
Initial release20132019
Current releasecloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)
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-types
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 indexesyesall fields are automatically indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)with Databricks SQLKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresPythonuser defined functions and aggregatesYes, possible languages: KQL, Python, R
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAzure Active Directory Authentication
More information provided by the system vendor
atotiDatabricksMicrosoft Azure Data Explorer
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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atotiDatabricksMicrosoft Azure Data Explorer
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