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

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

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  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.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 BigTableApache 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 storeRelational DBMSDocument storeWide column storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#278  Overall
#39  Key-value stores
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Websitewww.cloudflare.com/­developer-platform/­workers-kvwww.esgyn.cncloud.google.com/­datastorehbase.apache.orgignite.apache.org
Technical documentationdevelopers.cloudflare.com/­kv/­apicloud.google.com/­datastore/­docshbase.apache.org/­book.htmlapacheignite.readme.io/­docs
DeveloperCloudflareEsgynGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release20182015200820082015
Current release2.3.4, January 2021Apache Ignite 2.6
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaC++, Java, .Net
Server operating systemshostedLinuxhostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenoyesyes, details hereoptions to bring your own types, AVROyes
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.nonononoyes
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)noANSI-99 for query and DML statements, subset of DDL
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
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App Engineyes infoCoprocessors in Javayes (compute grid and cache interceptors can be used instead)
TriggersnonoCallbacks using the Google Apps Engineyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyesyes (compute grid and hadoop accelerator)
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnono
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)ACID
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.nononoyesyes
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 & ABACSecurity Hooks for custom implementations

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More resources
Cloudflare Workers KVEsgynDBGoogle Cloud DatastoreHBaseIgnite
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