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DBMS > Cloudflare Workers KV vs. FatDB vs. ScyllaDB vs. Spark SQL

System Properties Comparison Cloudflare Workers KV vs. FatDB vs. ScyllaDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonFatDB  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Cassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Key-value store
Wide column storeRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvwww.scylladb.comspark.apache.org/­sql
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCloudflareFatCloudScyllaDBApache Software Foundation
Initial release2018201220152014
Current releaseScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageC#C++Scala
Server operating systemshostedWindowsLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonono
Secondary indexesnoyesyes infocluster global secondary indicesno
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statements
APIs and other access methodsHTTP REST
Proprietary protocol
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C#For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infovia applicationsyes, Luano
Triggersnoyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication factor infoRepresentation of geographical distribution of servers is possiblenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operationsno
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.noyes infoin-memory tablesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users can be defined per objectno
More information provided by the system vendor
Cloudflare Workers KVFatDBScyllaDBSpark SQL
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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Cloudflare Workers KVFatDBScyllaDBSpark SQL
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