DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. EsgynDB vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. Percona Server for MongoDB vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.esgyn.cnwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynPerconaApache Software Foundation
Initial release2019201520152014
Current release3.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++Scala
Server operating systemshostedLinuxLinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC/ADO.NetActionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored ProceduresJavaScriptno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication between multi datacentersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infovia In-Memory Engineno
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users and rolesno

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
Amazon DocumentDBEsgynDBPercona Server for MongoDBSpark SQL
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

provided by Google News

5 Reasons to Run MongoDB on Kubernetes
6 March 2024, The New Stack

A New Way to Provision Databases on Kubernetes
21 March 2024, hackernoon.com

FerretDB goes GA: Gives you MongoDB, without the MongoDB...
15 May 2023, The Stack

Unlock MongoDB's Full Potential: Ensuring Post-Upgrade Success
22 February 2024, The New Stack

Percona launches management system aimed at open-source databases
17 May 2022, The Register

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here