DBMS > Amazon DynamoDB vs. Apache Druid vs. Geode vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Apache Druid vs. Geode vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Key-value store

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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

druid.apache.org

geode.apache.org

quasar.ai

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

geode.apache.org/docs

doc.quasar.ai/master

Developer

Amazon

Apache Software Foundation and contributors

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

quasardb

Initial release

2012

2002

2009

Current release

29.0.1, April 2024

1.1, February 2017

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

hosted

Linux
OS X
Unix

All OS with a Java VM

the JDK (8 or later) is also required

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL for querying

SQL-like query language (OQL)

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

Java Client API
Memcached protocol
RESTful HTTP API

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights per client and object definable

Cryptographically strong user authentication and audit trail

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