DBMS > Amazon DynamoDB vs. MongoDB vs. Spark SQL
System Properties Comparison Amazon DynamoDB vs. MongoDB vs. Spark SQL
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|Editorial information provided by DB-Engines|
|Name||Amazon DynamoDB Xexclude from comparison||MongoDB Xexclude from comparison||Spark SQL Xexclude from comparison|
|Description||Hosted, scalable database service by Amazon with the data stored in Amazons cloud||One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure||Spark SQL is a component on top of 'Spark Core' for structured data processing|
|Primary database model||Document store|
|Document store||Relational DBMS|
|Secondary database models||Spatial DBMS|
Search engine integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS Time Series Collections introduced in Release 5.0
|Developer||Amazon||MongoDB, Inc||Apache Software Foundation|
|Current release||6.0.1, August 2022||3.3.0 ( 2.13), June 2022|
|License Commercial or Open Source||commercial free tier for a limited amount of database operations||Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||yes||no MongoDB available as DBaaS (MongoDB Atlas)||no|
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|Server operating systems||hosted||Linux|
|Data scheme||schema-free||schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.||yes|
|Typing predefined data types such as float or date||yes||yes string, integer, double, decimal, boolean, date, object_id, geospatial||yes|
|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.||no|
|SQL Support of SQL||no||Read-only SQL queries via the MongoDB Connector for BI||SQL-like DML and DDL statements|
|APIs and other access methods||RESTful HTTP API||proprietary protocol using JSON||JDBC|
|Supported programming languages||.Net|
|Actionscript unofficial driver|
Clojure unofficial driver
ColdFusion unofficial driver
D unofficial driver
Dart unofficial driver
Delphi unofficial driver
Groovy unofficial driver
Lisp unofficial driver
Lua unofficial driver
MatLab unofficial driver
PowerShell unofficial driver
Prolog unofficial driver
R unofficial driver
Smalltalk unofficial driver
|Triggers||yes by integration with AWS Lambda||yes in MongoDB Atlas only||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.||yes, utilizing Spark Core|
|Replication methods Methods for redundantly storing data on multiple nodes||yes||Multi-Source deployments with MongoDB Atlas Global Clusters|
|MapReduce Offers an API for user-defined Map/Reduce methods||no may be implemented via Amazon Elastic MapReduce (Amazon EMR)||yes|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency|
Immediate Consistency can be specified for read operations
Immediate Consistency can be individually decided for each write operation
|Foreign keys Referential integrity||no||no typically not used, however similar functionality with DBRef possible||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID ACID across one or more tables within a single AWS account and region||Multi-document ACID Transactions with snapshot isolation||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes optional, enabled by default||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes In-memory storage engine introduced with MongoDB version 3.2||no|
|User concepts Access control||Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)||Access rights for users and roles||no|
More information provided by the system vendor
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|Related products and services|
|3rd parties||CData: Connect to Big Data & NoSQL through standard Drivers.|
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|Amazon DynamoDB||MongoDB||Spark SQL|
|DB-Engines blog posts|
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