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DBMS > Cloudflare Workers KV vs. Google Cloud Datastore vs. Riak KV vs. Sphinx

System Properties Comparison Cloudflare Workers KV vs. Google Cloud Datastore vs. Riak KV vs. Sphinx

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#283  Overall
#40  Key-value stores
Score4.13
Rank#71  Overall
#12  Document stores
Score3.84
Rank#76  Overall
#9  Key-value stores
Score5.97
Rank#56  Overall
#5  Search engines
Websitewww.cloudflare.com/­developer-platform/­workers-kvcloud.google.com/­datastoresphinxsearch.com
Technical documentationdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docs
DeveloperCloudflareGoogleOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release2018200820092001
Current release3.2.0, December 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC++
Server operating systemshostedhostedLinux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details herenono
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 indexesnoyesrestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)
APIs and other access methodsHTTP REST
Proprietary protocol
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnousing Google App EngineErlangno
TriggersnoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Securityno

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More resources
Cloudflare Workers KVGoogle Cloud DatastoreRiak KVSphinx
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