DBMS > Amazon DynamoDB vs. PouchDB vs. Realm vs. Solr vs. Transbase

System Properties Comparison Amazon DynamoDB vs. PouchDB vs. Realm vs. Solr vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

JavaScript DBMS with an API inspired by CouchDB

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

A widely used distributed, scalable search engine based on Apache Lucene

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Key-value store

Document store

Search engine

Relational DBMS

Secondary database models

Spatial 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	2.28
Rank	#115	Overall
	#21	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

aws.amazon.com/dynamodb

pouchdb.com

realm.io

solr.apache.org

www.transaction.de/en/products/transbase.html

Technical documentation

docs.aws.amazon.com/dynamodb

pouchdb.com/guides

realm.io/docs

solr.apache.org/resources.html

www.transaction.de/en/products/transbase/features.html

Developer

Amazon

Apache Software Foundation

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

Transaction Software GmbH

Initial release

2012

2014

2006

1987

Current release

7.1.1, June 2019

9.6.0, April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

commercial

free development license

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

JavaScript

Java

C and C++

Server operating systems

hosted

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

Android
Backend: server-less
iOS
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

via views

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Solr Parallel SQL Interface

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

runs within the applications so server-side scripts are unnecessary

Java plugins

yes

Triggers

yes

by integration with AWS Lambda

yes

Change Listeners

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

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

yes

fine grained access rights according to SQL-standard

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