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DBMS > Amazon DocumentDB vs. Databricks vs. etcd vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon DocumentDB vs. Databricks vs. etcd vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceThe 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 platform
Primary database modelDocument storeDocument store
Relational DBMS
Key-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
Score1.91
Rank#132  Overall
#24  Document stores
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
Websiteaws.amazon.com/­documentdbwww.databricks.cometcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­services/­data-explorer
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDatabricksMicrosoft
Initial release201920132019
Current release3.4, August 2019cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGo
Server operating systemshostedhostedFreeBSD
Linux
Windows infoexperimental
hosted
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyes 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.noyesnoyes
Secondary indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLnowith Databricks SQLnoKusto Query Language (KQL), SQL subset
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Python
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
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoYes, possible languages: KQL, Python, R
Triggersnoyes, watching key changesyes 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 nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesUsing 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnono
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.nonono
User concepts infoAccess controlAccess rights for users and rolesnoAzure Active Directory Authentication
More information provided by the system vendor
Amazon DocumentDBDatabricksetcdMicrosoft Azure Data Explorer
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon DocumentDBDatabricksetcdMicrosoft Azure Data Explorer
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