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

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Embeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational 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
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.databricks.comgoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.databricks.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDatabricksGoogleMicrosoft
Initial release201320142019
Current release2.1.12, February 2017cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScript
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safarihosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes 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.yesnoyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLSQL-like query language infovia JavaScript builder patternKusto 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
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoYes, possible languages: KQL, Python, R
TriggersUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes 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 integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDBno
User concepts infoAccess controlnoAzure Active Directory Authentication
More information provided by the system vendor
DatabricksLovefieldMicrosoft Azure Data Explorer
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLovefieldMicrosoft Azure Data Explorer
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