DBMS > Amazon DynamoDB vs. Apache Impala vs. EsgynDB vs. PouchDB vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. EsgynDB vs. PouchDB vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for Hadoop

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Document 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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

impala.apache.org/impala-docs.html

pouchdb.com/guides

doc.quasar.ai/master

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

Apache Software Foundation

quasardb

Initial release

2012

2013

2015

2012

2009

Current release

4.1.0, June 2022

7.1.1, June 2019

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

Open Source

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

C++

C++, Java

JavaScript

C++

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

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

via views

yes

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

View functions in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication between multi datacenters

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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)

yes

query execution via MapReduce

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

Eventual Consistency

Immediate Consistency

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

by using IndexedDB, WebSQL or LevelDB as backend

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)

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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