DBMS > Amazon DynamoDB vs. Cloudflare Workers KV vs. HBase vs. Ignite

System Properties Comparison Amazon DynamoDB vs. Cloudflare Workers KV vs. HBase vs. Ignite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Apache 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 model

Document store
Key-value store

Key-value store

Wide column store

Key-value store
Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

aws.amazon.com/dynamodb

www.cloudflare.com/developer-platform/workers-kv

hbase.apache.org

ignite.apache.org

Technical documentation

docs.aws.amazon.com/dynamodb

developers.cloudflare.com/kv/api

hbase.apache.org/book.html

apacheignite.readme.io/docs

Developer

Amazon

Cloudflare

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

Initial release

2012

2018

2008

2015

Current release

2.3.4, January 2021

Apache Ignite 2.6

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java, .Net

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

RESTful HTTP API

HTTP REST
Proprietary protocol

Java API
RESTful HTTP API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by integration with AWS Lambda

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Security Hooks for custom implementations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.