DBMS > Amazon DocumentDB vs. EsgynDB vs. GridGain vs. NSDb

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. GridGain vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

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

GridGain is an in-memory computing platform, built on Apache Ignite

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

Primary database model

Document store

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/documentdb

www.esgyn.cn

www.gridgain.com

nsdb.io

Technical documentation

aws.amazon.com/documentdb/resources

www.gridgain.com/docs/index.html

nsdb.io/Architecture

Developer

Esgyn

GridGain Systems, Inc.

Initial release

2019

2015

2007

2017

Current release

GridGain 8.5.1

License

Commercial or Open Source

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java, C++, .Net

Java, Scala

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC
HTTP REST
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Java
PHP
Python
Ruby
Scala

Java
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

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 Apache Lucene

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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More resources

Recent citations in the news

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 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 Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

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

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
16 April 2024, AWS Blog

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