DBMS > Amazon DocumentDB vs. Apache Impala vs. JSqlDb vs. OrigoDB

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. JSqlDb vs. OrigoDB

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Analytic DBMS for Hadoop

JavaScript Query Language Database, stores JavaScript objects and primitives

A fully ACID in-memory object graph database

Primary database model

Document store

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Website

aws.amazon.com/documentdb

impala.apache.org

jsqldb.org (offline)

origodb.com

Technical documentation

aws.amazon.com/documentdb/resources

impala.apache.org/impala-docs.html

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Konrad von Backstrom

Robert Friberg et al

Initial release

2019

2013

2018

2009

under the name LiveDB

Current release

4.1.0, June 2022

0.8, December 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

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++

Server operating systems

hosted

Linux

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

JavaScript

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

functions in JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

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

depending on model

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 RocksDB

yes

Write ahead log

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role based authorization

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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

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

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20 May 2024, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

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28 November 2017, SDTimes.com

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28 November 2017, Datanami

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24 June 2022, InfoWorld

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provided by Google News

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