DBMS > Datastax Enterprise vs. MongoDB vs. PostGIS
System Properties Comparison Datastax Enterprise vs. MongoDB vs. PostGIS
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|Editorial information provided by DB-Engines
|Datastax Enterprise Xexclude from comparison
|MongoDB Xexclude from comparison
|PostGIS Xexclude from comparison
|DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.
|One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
|Spatial extension of PostgreSQL
|Primary database model
|Wide column store
|Secondary database models
Search engine integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS Time Series Collections introduced in Release 5.0
Vector DBMS currently available in the MongoDB Atlas cloud service only
|6.8, April 2020
|6.0.7, June 2023
|3.3.4, July 2023
|License Commercial or Open Source
|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 GPL v2.0
|Cloud-based only Only available as a cloud service
|no MongoDB available as DBaaS (MongoDB Atlas)
|DBaaS offerings (sponsored links) Database as a Service
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|Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
|MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
|Server operating systems
|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.
|Typing predefined data types such as float or date
|yes string, integer, double, decimal, boolean, date, object_id, geospatial
|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.
|SQL Support of SQL
|SQL-like DML and DDL statements (CQL); Spark SQL
|Read-only SQL queries via the MongoDB Atlas SQL Interface
|APIs and other access methods
|Proprietary protocol CQL (Cassandra Query Language)
TinkerPop Gremlin with DSE Graph
proprietary protocol using JSON
|Supported programming languages
|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
|Server-side scripts Stored procedures
|user defined functions
|yes in MongoDB Atlas only
|Partitioning methods Methods for storing different data on different nodes
|Sharding no "single point of failure"
|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 based on PostgreSQL
|Replication methods Methods for redundantly storing data on multiple nodes
|configurable replication factor, datacenter aware, advanced replication for edge computing
|Multi-Source deployments with MongoDB Atlas Global Clusters
|yes based on PostgreSQL
|MapReduce Offers an API for user-defined Map/Reduce methods
|Consistency concepts Methods to ensure consistency in a distributed system
Tunable Consistency consistency level can be individually decided with each write operation
|Eventual Consistency can be individually decided for each read operation
Immediate Consistency default behaviour
|Foreign keys Referential integrity
|no typically not used, however similar functionality with DBRef possible
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|no Atomicity and isolation are supported for single operations
|Multi-document ACID Transactions with snapshot isolation
|Concurrency Support for concurrent manipulation of data
|Durability Support for making data persistent
|yes optional, enabled by default
|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
|User concepts Access control
|Access rights for users can be defined per object
|Access rights for users and roles
|yes based on PostgreSQL
|More information provided by the system vendor
|DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
|MongoDB provides an integrated suite of cloud database and data services to accelerate...
|Supporting the following application requirements: Zero downtime - Built on Apache...
|Built around the flexible document data model and unified API, MongoDB is a developer...
|Typical application scenarios
|Applications that must be massively and linearly scalable with 100% uptime and able...
|AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
|Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
|ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
|Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
|Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
|Licensing and pricing models
|MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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