DBMS > Amazon DynamoDB vs. Heroic vs. Percona Server for MongoDB vs. Quasardb vs. Realm

System Properties Comparison Amazon DynamoDB vs. Heroic vs. Percona Server for MongoDB vs. Quasardb vs. Realm

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, high-performance timeseries database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store
Key-value store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

aws.amazon.com/dynamodb

github.com/spotify/heroic

www.percona.com/mongodb/software/percona-server-for-mongodb

quasar.ai

realm.io

Technical documentation

docs.aws.amazon.com/dynamodb

spotify.github.io/heroic

docs.percona.com/percona-distribution-for-mongodb

doc.quasar.ai/master

realm.io/docs

Developer

Amazon

Spotify

Percona

quasardb

Realm, acquired by MongoDB in May 2019

Initial release

2012

2014

2015

2009

2014

Current release

3.4.10-2.10, November 2017

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

GPL Version 2

commercial

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

Open Source

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

BSD
Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

via Elasticsearch

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

proprietary protocol using JSON

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

by integration with AWS Lambda

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

via In-Memory Engine

yes

Transient mode

yes

In-Memory realm

User concepts

Access control

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

Access rights for users and roles

Cryptographically strong user authentication and audit trail

yes

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