DBMS > Amazon DocumentDB vs. Datomic vs. NSDb vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. Datomic vs. NSDb vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

aws.amazon.com/documentdb

www.datomic.com

nsdb.io

wakanda.github.io

Technical documentation

aws.amazon.com/documentdb/resources

docs.datomic.com

nsdb.io/Architecture

wakanda.github.io/doc

Developer

Cognitect

Wakanda SAS

Initial release

2019

2012

2017

2012

Current release

1.0.7075, December 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2.0

Open Source

AGPLv3, extended commercial license available

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

Java, Clojure

Java, Scala

C++, JavaScript

Server operating systems

hosted

All OS with a Java VM

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java

Java
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

But extensive use of caching in the application peers

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

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)

Using Apache Lucene

yes

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster | Amazon Web Services
4 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

provided by Google News

Nubank buys firm behind Clojure programming language
28 July 2020, Finextra

Architecting Software for Leverage
13 November 2021, InfoQ.com

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

James Dixon Imagines A Data Lake That Matters
26 January 2015, Forbes

Zoona Case Study
16 December 2017, AWS Blog

provided by Google News

Share this page