DBMS > Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. Teradata Aster
System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. MongoDB vs. PostgreSQL vs. Teradata Aster
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Google Cloud Datastore Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | MongoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | Teradata Aster Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform | Fully managed big data interactive analytics platform | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Platform for big data analytics on multistructured data sources and types | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Relational DBMS column oriented | Document store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS 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 | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | cloud.google.com/datastore | azure.microsoft.com/services/data-explorer | www.mongodb.com | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cloud.google.com/datastore/docs | docs.microsoft.com/en-us/azure/data-explorer | www.mongodb.com/docs/manual | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | MongoDB, Inc | PostgreSQL Global Development Group www.postgresql.org/developer | Teradata | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 2019 | 2009 | 1989 1989: Postgres, 1996: PostgreSQL | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 6.0.7, June 2023 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | 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 BSD | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | yes | no MongoDB available as DBaaS (MongoDB Atlas) | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | hosted | Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | Fixed schema with schema-less datatypes (dynamic) | 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 | Flexible Schema (defined schema, partial schema, schema free) defined schema within the relational store; partial schema or schema free in the Aster File Store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes, details here | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes string, integer, double, decimal, boolean, date, object_id, geospatial | yes | 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 | yes | yes specific XML-type available, but no XML query functionality. | yes in Aster File Store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language (GQL) | Kusto Query Language (KQL), SQL subset | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes standard with numerous extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC (using protocol buffers) API RESTful HTTP/JSON API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC ODBC OLE DB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Go Java JavaScript (Node.js) PHP Python Ruby | .Net Go Java JavaScript (Node.js) PowerShell Python R | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Java Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | using Google App Engine | Yes, possible languages: KQL, Python, R | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | R packages | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | Callbacks using the Google Apps Engine | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes in MongoDB Atlas only | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding Implicit feature of the cloud service | 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. | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication using Paxos | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | yes Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes using Google Cloud Dataflow | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | yes SQL Map-Reduce Framework | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent. | Eventual Consistency Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | Immediate Consistency or Eventual Consistency depending on configuration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes via ReferenceProperties or Ancestor paths | no | no typically not used, however similar functionality with DBRef possible | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID Serializable Isolation within Transactions, Read Committed outside of Transactions | no | Multi-document ACID Transactions with snapshot isolation | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optional, enabled by default | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes In-memory storage engine introduced with MongoDB version 3.2 | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Azure Active Directory Authentication | Access rights for users and roles | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Datastore | Microsoft Azure Data Explorer | MongoDB | PostgreSQL | Teradata Aster | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Built around the flexible document data model and unified API, MongoDB is a developer... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more Studio 3T: The world's favorite IDE for working with MongoDB » more | CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more Redgate webinars: A series of key topics for new PostgreSQL users. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today! » more pgDash: In-Depth PostgreSQL Monitoring. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Datastore | Microsoft Azure Data Explorer | MongoDB | PostgreSQL | Teradata Aster | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Google Cloud Platform: Professional Data Engineer certification prep Google Cloud Stops Exit Fees Best cloud storage of 2024 Inside Google’s strategic move to eliminate customer cloud data transfer fees BigID Data Intelligence Platform Now Available on Google Cloud Marketplace provided by Google News | We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News | Alger Mid Cap Growth Fund Maintains its Conviction in MongoDB (MDB) Unpacking the Latest Options Trading Trends in MongoDB - MongoDB (NASDAQ:MDB) Bendigo and Adelaide Bank Partners with MongoDB to Modernize Core Banking Technology Using Generative AI Should You Buy MongoDB, Snowflake, and Atlassian at Their 52-Week Lows? MongoDB loses nearly a quarter of its value after adjusting revenue forecasts provided by Google News | Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions provided by Google News | Teradata Enhances Big Data Analytics Platform Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business Teradata's Aster shows how the flowers of fraud bloom Case study: Siemens reduces train failures with Teradata Aster Teradata unveils improved QueryGrid connectors provided by Google News |
Share this page