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DBMS > Amazon DocumentDB vs. EsgynDB

System Properties Comparison Amazon DocumentDB vs. EsgynDB

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Our visitors often compare Amazon DocumentDB and EsgynDB with HBase and PostgreSQL.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEsgynDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEnterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion
Primary database modelDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.68
Rank#183  Overall
#27  Document stores
Score0.19
Rank#266  Overall
#123  Relational DBMS
Websiteaws.amazon.com/­documentdbesgyn.com
Technical documentationaws.amazon.com/­documentdb/­resourcesesgyn.com/­developers
DeveloperEsgyn
Initial release20192015
License infoCommercial or Open Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java
Server operating systemshostedLinux
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesyes
SQL infoSupport of SQLnoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoJava Stored Procedures
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMaster-master replication between multi datacenters
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBEsgynDB
Recent citations in the news

12 things you should know about Amazon DocumentDB (with MongoDB compatibility)
19 May 2020, idk.dev

Introducing role-based access control for Amazon DocumentDB (with MongoDB compatibility)
27 April 2020, idk.dev

Deploying a serverless application using AWS CDK
15 May 2020, idk.dev

Getting Started with Amazon DocumentDB (with MongoDB compatibility); Part 2 – using AWS Cloud9
24 April 2020, idk.dev

AWS Announces Amazon DocumentDB (with MongoDB Compatibility)
9 January 2019, Business Wire

provided by Google News

Esgyn Strato: Esgyn announces a Hybrid / Multi Cloud Big Data Platform Service to run and optimize your b..
30 November 2018, Markets Insider

Mphasis partners with Esgyn Corporation to provide specialized solutions to clients looking to harness big data
7 June 2019, Moneycontrol

The Apache Software Foundation Announces Apache® Trafodion™ as a Top-Level Project
10 January 2018, GlobeNewswire

Mphasis partners with Esgyn Corporation to optimize Open-Source frameworks and expand industry footprint
24 May 2019, PRNewswire

Esgyn Corporation and Ampool Partner to Bring In-Memory Optimized Operational, Transactional and Real-Time Analytics to Hadoop.
18 May 2017, PR Newswire

provided by Google News

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