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DBMS > Cloudflare Workers KV vs. GridDB vs. Heroic vs. Spark SQL vs. YDB

System Properties Comparison Cloudflare Workers KV vs. GridDB vs. Heroic vs. Spark SQL vs. YDB

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonGridDB  Xexclude from comparisonHeroic  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.Scalable in-memory time series database optimized for IoT and Big DataTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpark 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 DBMSTime Series DBMSRelational DBMSDocument store
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#274  Overall
#39  Key-value stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series 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-kvgriddb.netgithub.com/­spotify/­heroicspark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.griddb.netspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperCloudflareToshiba CorporationSpotifyApache Software FoundationYandex
Initial release20182013201420142019
Current release5.1, August 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaScala
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.nonononono
Secondary indexesnoyesyes infovia Elasticsearchnoyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsHTTP REST
Proprietary protocol
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnonononono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesnoneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnonoACID
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.noyesnonono
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess rights defined for Yandex Cloud users
More information provided by the system vendor
Cloudflare Workers KVGridDBHeroicSpark SQLYDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Cloudflare Workers KVGridDBHeroicSpark SQLYDB
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