DBMS > Amazon DynamoDB vs. Drizzle vs. Ignite vs. KairosDB

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. Ignite vs. KairosDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

aws.amazon.com/dynamodb

ignite.apache.org

github.com/kairosdb/kairosdb

Technical documentation

docs.aws.amazon.com/dynamodb

apacheignite.readme.io/docs

kairosdb.github.io

Developer

Amazon

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Initial release

2012

2008

2015

2013

Current release

7.2.4, September 2012

Apache Ignite 2.6

1.2.2, November 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

Open Source

Apache 2.0

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

C++

C++, Java, .Net

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

with proprietary extensions

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

APIs and other access methods

RESTful HTTP API

JDBC

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

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

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

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

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

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

simple password-based access control

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