DBMS > Amazon DynamoDB vs. Apache Druid vs. HarperDB vs. Oracle Coherence

System Properties Comparison Amazon DynamoDB vs. Apache Druid vs. HarperDB vs. Oracle Coherence

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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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Oracles in-memory data grid solution

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Document store

Key-value store

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

aws.amazon.com/dynamodb

druid.apache.org

www.harperdb.io

www.oracle.com/java/coherence

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

docs.harperdb.io/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Amazon

Apache Software Foundation and contributors

HarperDB

Oracle

Initial release

2012

2017

2007

Current release

29.0.1, April 2024

3.1, August 2021

14.1, August 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

commercial

free community edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Node.js

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux
OS X

All OS with a Java VM

Data scheme

schema-free

yes

schema-less columns are supported

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like data manipulation statements

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
C++
Java

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Triggers

yes

by integration with AWS Lambda

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

yes

the nodes on which a table resides can be defined

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

Atomic execution of specific operations

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

optionally

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)

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

Access rights for users and roles

authentification to access the cache via certificates or http basic authentication

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