DBMS > Amazon DynamoDB vs. EsgynDB vs. FeatureBase vs. LevelDB

System Properties Comparison Amazon DynamoDB vs. EsgynDB vs. FeatureBase vs. LevelDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Primary database model

Document store
Key-value store

Relational DBMS

Key-value 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	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Website

aws.amazon.com/dynamodb

www.esgyn.cn

www.featurebase.com

github.com/google/leveldb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.featurebase.com

github.com/google/leveldb/blob/main/doc/index.md

Developer

Amazon

Esgyn

Molecula and Pilosa Open Source Contributors

Google

Initial release

2012

2015

2017

2011

Current release

2022, May 2022

1.23, February 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

BSD

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

C++

Server operating systems

hosted

Linux

Linux
macOS

Illumos
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

yes

SQL queries

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
JDBC
Kafka Connector
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

none

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

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

with automatic compression on writes

In-memory capabilities

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

yes

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

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