DBMS > Amazon DocumentDB vs. etcd vs. Google Cloud Firestore vs. Hive vs. PostgreSQL
System Properties Comparison Amazon DocumentDB vs. etcd vs. Google Cloud Firestore vs. Hive vs. PostgreSQL
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Amazon DocumentDB Xexclude from comparison | etcd Xexclude from comparison | Google Cloud Firestore Xexclude from comparison | Hive Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Fast, scalable, highly available, and fully managed MongoDB-compatible database service | A distributed reliable key-value store | Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products. | data warehouse software for querying and managing large distributed datasets, built on Hadoop | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store | Key-value store | Document store | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/documentdb | etcd.io github.com/etcd-io/etcd | firebase.google.com/products/firestore | hive.apache.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | aws.amazon.com/documentdb/resources | etcd.io/docs github.com/etcd-io/etcd/tree/master/Documentation | firebase.google.com/docs/firestore | cwiki.apache.org/confluence/display/Hive/Home | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Apache Software Foundation initially developed by Facebook | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2019 | 2017 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 3.4, August 2019 | 3.1.3, April 2022 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source Apache Version 2.0 | commercial | Open Source Apache Version 2 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Go | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | FreeBSD Linux Windows experimental | hosted | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | yes | 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 | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | no | no | SQL-like DML and DDL statements | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | proprietary protocol using JSON (MongoDB compatible) | gRPC JSON over HTTP | Android gRPC (using protocol buffers) API iOS JavaScript API RESTful HTTP API | JDBC ODBC Thrift | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | Go Java JavaScript (Node.js) PHP Python | .Net C C++ Clojure Erlang Go Haskell Java JavaScript (Node.js) Perl PHP Python R Ruby Rust Scala Tcl | Go Java JavaScript JavaScript (Node.js) Objective-C Python | C++ Java PHP Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | no | yes, Firebase Rules & Cloud Functions | yes user defined functions and integration of map-reduce | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes, watching key changes | yes, with Cloud Functions | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas | Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas. | Multi-source replication | selectable replication factor | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | Using Cloud Dataflow | yes query execution via MapReduce | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no typically not used, however similar functionality with DBRef possible | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic single-document operations | no | yes | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles | no | Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth. | Access rights for users, groups and roles | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DocumentDB | etcd | Google Cloud Firestore | Hive | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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