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DBMS > Databricks vs. etcd vs. Microsoft Azure Data Explorer vs. Vitess

System Properties Comparison Databricks vs. etcd vs. Microsoft Azure Data Explorer vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVitess  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.A distributed reliable key-value storeFully managed big data interactive analytics platformScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMS infocolumn orientedRelational 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
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­services/­data-explorervitess.io
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docs
DeveloperDatabricksMicrosoftThe Linux Foundation, PlanetScale
Initial release201320192013
Current release3.4, August 2019cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoGo
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
hostedDocker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-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.yesnoyes
Secondary indexesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLnoKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoYes, possible languages: KQL, Python, Ryes infoproprietary syntax
Triggersyes, watching key changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
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 nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nononoyes
User concepts infoAccess controlnoAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksetcdMicrosoft Azure Data ExplorerVitess
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksetcdMicrosoft Azure Data ExplorerVitess
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