DBMS > Amazon DocumentDB vs. ITTIA vs. Oracle NoSQL

System Properties Comparison Amazon DocumentDB vs. ITTIA vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store

Time Series DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.76
Rank	#128	Overall
	#24	Document stores

Score	0.45
Rank	#254	Overall
	#21	Time Series DBMS

Score	3.35
Rank	#78	Overall
	#13	Document stores
	#10	Key-value stores
	#42	Relational DBMS

Website

aws.amazon.com/documentdb

www.ittia.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

aws.amazon.com/documentdb/resources

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

ITTIA L.L.C.

Oracle

Initial release

2019

2007

2011

Current release

8.7

24.4, December 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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 and C++

Java

Server operating systems

hosted

Linux
Windows

Linux
Solaris SPARC/x86

Data scheme

schema-free

Fixed schema

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

optional

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-like DML and DDL statements

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
RESTful HTTP API
WebSocket

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
JavaScript (Node.js)
Python

C#
Go
Java
JavaScript (Node.js)
Python
Rust
Typescript (Node.js)

Server-side scripts

Stored procedures

yes

Triggers

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

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

yes

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

off heap cache

User concepts

Access control

Access rights for users and roles

Database file passwords

Access rights for users and roles

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