DBMS > Amazon DynamoDB vs. Databricks vs. EsgynDB vs. Realm vs. ToroDB

System Properties Comparison Amazon DynamoDB vs. Databricks vs. EsgynDB vs. Realm vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Relational DBMS

Document store

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Website

aws.amazon.com/dynamodb

www.databricks.com

www.esgyn.cn

realm.io

github.com/torodb/server

Technical documentation

docs.aws.amazon.com/dynamodb

docs.databricks.com

realm.io/docs

Developer

Amazon

Databricks

Esgyn

Realm, acquired by MongoDB in May 2019

8Kdata

Initial release

2012

2013

2015

2014

2016

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

AGPL-V3

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++, Java

Java

Server operating systems

hosted

Linux

Android
Backend: server-less
iOS
Windows

All OS with a Java 7 VM

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

with Databricks SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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

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

In-memory capabilities

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

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)

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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