DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. MongoDB vs. PostgreSQL vs. TigerGraph
System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. MongoDB vs. PostgreSQL vs. TigerGraph
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Name | Google Cloud Datastore Xexclude from comparison | Microsoft Azure Table Storage Xexclude from comparison | MongoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | TigerGraph Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform | A Wide Column Store for rapid development using massive semi-structured datasets | 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 | A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store | Wide column store | Document store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Graph 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 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cloud.google.com/datastore | azure.microsoft.com/en-us/services/storage/tables | www.mongodb.com | www.postgresql.org | www.tigergraph.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cloud.google.com/datastore/docs | www.mongodb.com/docs/manual | www.postgresql.org/docs | docs.tigergraph.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | MongoDB, Inc | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 2012 | 2009 | 1989 1989: Postgres, 1996: PostgreSQL | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | 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 | 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 | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes, details here | yes | 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 | no | yes specific XML-type available, but no XML query functionality. | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language (GQL) | no | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes standard with numerous extensions | SQL-like query language (GSQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC (using protocol buffers) API RESTful HTTP/JSON API | RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC native C library ODBC streaming API for large objects | GSQL (TigerGraph Query Language) Kafka RESTful HTTP/JSON API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Go Java JavaScript (Node.js) PHP Python Ruby | .Net C# C++ Java JavaScript (Node.js) PHP Python Ruby | 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++ Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | using Google App Engine | no | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | Callbacks using the Google Apps Engine | no | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes using Google Cloud Dataflow | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes via ReferenceProperties or Ancestor paths | no | no typically not used, however similar functionality with DBRef possible | yes | yes Relationships in graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID Serializable Isolation within Transactions, Read Committed outside of Transactions | optimistic locking | 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) | Access rights based on private key authentication or shared access signatures | Access rights for users and roles | fine grained access rights according to SQL-standard | Role-based access control | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Datastore | Microsoft Azure Table Storage | MongoDB | PostgreSQL | TigerGraph | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Datastore | Microsoft Azure Table Storage | MongoDB | PostgreSQL | TigerGraph | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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