DBMS > Amazon DocumentDB vs. Apache Druid vs. Datomic

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. Datomic

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Primary database model

Document store

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Website

aws.amazon.com/documentdb

druid.apache.org

www.datomic.com

Technical documentation

aws.amazon.com/documentdb/resources

druid.apache.org/docs/latest/design

docs.datomic.com

Developer

Apache Software Foundation and contributors

Cognitect

Initial release

2019

2012

Current release

29.0.1, April 2024

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

limited edition free

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

Java, Clojure

Server operating systems

hosted

Linux
OS X
Unix

All OS with a Java VM

Data scheme

schema-free

yes

schema-less columns are supported

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

But extensive use of caching in the application peers

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes, via HDFS, S3 or other storage engines

none

But extensive use of caching in the application peers

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Access rights for users and roles

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

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More resources

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