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DBMS > Cloudflare Workers KV vs. Heroic vs. Microsoft Azure Data Explorer vs. Spark SQL vs. YDB

System Properties Comparison Cloudflare Workers KV vs. Heroic vs. Microsoft Azure Data Explorer vs. Spark SQL vs. YDB

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value storeTime Series DBMSRelational DBMS infocolumn orientedRelational DBMSDocument store
Relational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#274  Overall
#39  Key-value stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdevelopers.cloudflare.com/­kv/­apispotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperCloudflareSpotifyMicrosoftApache Software FoundationYandex
Initial release20182014201920142019
Current releasecloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemshostedhostedLinux
OS X
Windows
Linux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesnono
Secondary indexesnoyes infovia Elasticsearchall fields are automatically indexednoyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsHTTP REST
Proprietary protocol
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnono
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononono
User concepts infoAccess controlAzure Active Directory AuthenticationnoAccess rights defined for Yandex Cloud users

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More resources
Cloudflare Workers KVHeroicMicrosoft Azure Data ExplorerSpark SQLYDB
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