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DBMS > Cloudflare Workers KV vs. Google Cloud Datastore vs. GridGain vs. Ignite

System Properties Comparison Cloudflare Workers KV vs. Google Cloud Datastore vs. GridGain vs. Ignite

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonIgnite  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 PlatformGridGain is an in-memory computing platform, built on Apache IgniteApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelKey-value storeDocument storeKey-value store
Relational DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvcloud.google.com/­datastorewww.gridgain.comignite.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlapacheignite.readme.io/­docs
DeveloperCloudflareGoogleGridGain Systems, Inc.Apache Software Foundation
Initial release2018200820072015
Current releaseGridGain 8.5.1Apache Ignite 2.6
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
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 languageJava, C++, .NetC++, Java, .Net
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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.nonoyesyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsHTTP REST
Proprietary protocol
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)yes (compute grid and cache interceptors can be used instead)
TriggersnoCallbacks using the Google Apps Engineyes (cache interceptors and events)yes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes (replicated cache)yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yes (compute grid and hadoop accelerator)
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsSecurity Hooks for custom implementations

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More resources
Cloudflare Workers KVGoogle Cloud DatastoreGridGainIgnite
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