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DBMS > Cloudflare Workers KV vs. EsgynDB vs. Google Cloud Datastore vs. HBase

System Properties Comparison Cloudflare Workers KV vs. EsgynDB vs. Google Cloud Datastore vs. HBase

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelKey-value storeRelational DBMSDocument storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.cloudflare.com/­developer-platform/­workers-kvwww.esgyn.cncloud.google.com/­datastorehbase.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docshbase.apache.org/­book.html
DeveloperCloudflareEsgynGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2018201520082008
Current release2.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava
Server operating systemshostedLinuxhostedLinux
Unix
Windows infousing Cygwin
Data schemeschema-freeyesschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or datenoyesyes, details hereoptions to bring your own types, AVRO
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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyesSQL-like query language (GQL)no
APIs and other access methodsHTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App Engineyes infoCoprocessors in Java
TriggersnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 Consistency or Eventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Cloudflare Workers KVEsgynDBGoogle Cloud DatastoreHBase
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