DBMS > Amazon DynamoDB vs. Datomic vs. Kyligence Enterprise vs. NSDb

System Properties Comparison Amazon DynamoDB vs. Datomic vs. Kyligence Enterprise vs. NSDb

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A distributed analytics engine for big data, built on top of Apache Kylin

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store
Key-value store

Relational DBMS

Time Series 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.datomic.com

kyligence.io/kyligence-enterprise

nsdb.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.datomic.com

nsdb.io/Architecture

Developer

Amazon

Cognitect

Kyligence, Inc.

Initial release

2012

2016

2017

Current release

1.0.6735, June 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

Java, Scala

Server operating systems

hosted

All OS with a Java VM

Linux

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

Java
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

yes

by integration with AWS Lambda

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

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

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