DBMS > Amazon Aurora vs. Couchbase vs. PostgreSQL vs. PouchDB vs. Spark SQL
System Properties Comparison Amazon Aurora vs. Couchbase vs. PostgreSQL vs. PouchDB vs. Spark SQL
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Name | Amazon Aurora Xexclude from comparison | Couchbase Originally called Membase Xexclude from comparison | PostgreSQL Xexclude from comparison | PouchDB Xexclude from comparison | Spark SQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | MySQL and PostgreSQL compatible cloud service by Amazon | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | JavaScript DBMS with an API inspired by CouchDB | Spark SQL is a component on top of 'Spark Core' for structured data processing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Document store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Document store | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/rds/aurora | www.couchbase.com | www.postgresql.org | pouchdb.com | spark.apache.org/sql | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | docs.couchbase.com | www.postgresql.org/docs | pouchdb.com/guides | spark.apache.org/docs/latest/sql-programming-guide.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Couchbase, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | Apache Software Foundation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2011 | 1989 1989: Postgres, 1996: PostgreSQL | 2012 | 2014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 16.3, May 2024 | 7.1.1, June 2019 | 3.5.0 ( 2.13), September 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source BSD | Open Source | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C, C++, Go and Erlang | C | JavaScript | Scala | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | server-less, requires a JavaScript environment (browser, Node.js) | Linux OS X Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | no | 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. | yes | yes specific XML-type available, but no XML query functionality. | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes via views | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes standard with numerous extensions | no | SQL-like DML and DDL statements | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET JDBC native C library ODBC streaming API for large objects | HTTP REST only for PouchDB Server JavaScript API | JDBC ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | JavaScript | Java Python R Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | View functions in JavaScript | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes via the TAP protocol | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Automatic Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding with a proxy-based framework, named couchdb-lounge | yes, utilizing Spark Core | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | Multi-source replication including cross data center replication Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication also with CouchDB databases Source-replica replication also with CouchDB databases | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Immediate Consistency | Eventual Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes by using IndexedDB, WebSQL or LevelDB as backend | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes Ephemeral buckets | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | fine grained access rights according to SQL-standard | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon Aurora | Couchbase Originally called Membase | PostgreSQL | PouchDB | Spark SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Amazon - the rising star in the DBMS market | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | 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 | New kids on the block: database management systems implemented in JavaScript | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ... Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services Join the preview of Amazon Aurora Limitless Database | Amazon Web Services Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ... Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... provided by Google News | A Closer Look at 9 Analyst Recommendations For Couchbase Database company Couchbase cruises to another solid earnings and revenue beat Couchbase, Inc. (NASDAQ:BASE) Shares Slammed 29% But Getting In Cheap Might Be Difficult Regardless Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase (NASDAQ:BASE) Price Target Lowered to $30.00 at DA Davidson provided by Google News | PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features How to implement a better like, views, comment counters in PostgreSQL? provided by Google News | Building an Offline First App with PouchDB — SitePoint Create Offline Web Apps Using Service Workers & PouchDB — SitePoint 3 Reasons To Think Offline First Getting Started with PouchDB Client-Side JavaScript Database — SitePoint Offline-first web and mobile apps: Top frameworks and components provided by Google News | Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services What is Apache Spark? The big data platform that crushed Hadoop Performance Insights from Sigma Rule Detections in Spark Streaming Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024 Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM) provided by Google News |
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