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DBMS > Databricks vs. Heroic vs. LMDB vs. Microsoft Azure Data Explorer

System Properties Comparison Databricks vs. Heroic vs. LMDB vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonLMDB  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA high performant, light-weight, embedded key-value database libraryFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Time Series DBMSKey-value storeRelational 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.databricks.comgithub.com/­spotify/­heroicwww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.databricks.comspotify.github.io/­heroicwww.lmdb.tech/­docdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDatabricksSpotifySymasMicrosoft
Initial release2013201420112019
Current release0.9.32, January 2024cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemshostedLinux
Unix
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeFixed 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.yesnonoyes
Secondary indexesyesyes infovia Elasticsearchnoall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoAzure Active Directory Authentication
More information provided by the system vendor
DatabricksHeroicLMDBMicrosoft Azure Data Explorer
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHeroicLMDBMicrosoft Azure Data Explorer
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