DBMS > Couchbase vs. NuoDB vs. PlanetScale vs. Postgres-XL vs. PostgreSQL
System Properties Comparison Couchbase vs. NuoDB vs. PlanetScale vs. Postgres-XL vs. PostgreSQL
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Couchbase  Originally called Membase Xexclude from comparison | NuoDB Xexclude from comparison | PlanetScale Xexclude from comparison | Postgres-XL Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | NuoDB is a webscale distributed database that supports SQL and ACID transactions | Scalable, distributed, serverless MySQL database platform built on top of Vitess | Based on PostgreSQL enhanced with MPP and write-scale-out cluster features | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store | Relational DBMS | Relational DBMS | 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 | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extensionSearch engine Time Series DBMS Vector DBMS | Document store Spatial DBMS | Document store Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.couchbase.com | www.3ds.com/nuodb-distributed-sql-database | planetscale.com | www.postgres-xl.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.couchbase.com | doc.nuodb.com | planetscale.com/docs | www.postgres-xl.org/documentation | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Couchbase, Inc. | Dassault Systèmes originally NuoDB, Inc. | PlanetScale | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 2013 | 2020 | 2014 since 2012, originally named StormDB | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 10 R1, October 2018 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Business Source License (BSL 1.1); Commercial licenses also available | commercial limited edition free | commercial | Open Source Mozilla public license | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | 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 | C, C++, Go and Erlang | C++ | Go | C | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Windows | hosted Amazon EC2, Windows Azure, SoftLayer Linux OS X Windows | Docker Linux macOS | Linux macOS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | 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 | yes XML type, but no XML query functionality | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes | yes with proprietary extensions | yes distributed, parallel query execution | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET JDBC ODBC | ADO.NET JDBC MySQL protocol ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C Go Java JavaScript Node.jsKotlin PHP Python Ruby Scala | .Net C C++ Go Java JavaScript JavaScript (Node.js) PHP Python Ruby | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | Java, SQL | yes proprietary syntax | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes via the TAP protocol | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Automatic Sharding | data is dynamically stored/cached on the nodes where it is read/written | Sharding | horizontal partitioning | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication including cross data center replication Source-replica replication | yes Managed transparently by NuoDB | Multi-source replication 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 | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Immediate Consistency | Eventual Consistency across shards Immediate Consistency within a shard | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | yes not for MyISAM storage engine | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID tunable commit protocol | ACID at shard level | ACID MVCC | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes MVCC | yes table locks or row locks depending on storage engine | 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. | yes Ephemeral buckets | yes Temporary table | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | Standard SQL roles/ privileges, Administrative Users | Users with fine-grained authorization concept no user groups or roles | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more | Redgate webinars: A series of key topics for new PostgreSQL users.
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| Couchbase Originally called Membase | NuoDB | PlanetScale | Postgres-XL | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | Meet some database management systems you are likely to hear more about in the future | 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 Monitoring PostgreSQL with Redgate Monitor Q4 Earnings Highs And Lows: Couchbase (NASDAQ:BASE) Vs The Rest Of The Data Storage Stocks Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase's revenue grows 20% and its stock rises in extended trading Short Interest in Couchbase, Inc. (NASDAQ:BASE) Increases By 13.6% Couchbase Server and Capella to gain vector support provided by Google News Paul DiLaura of Dassault Systemes Joins NuoDB Board of Directors Paul DiLaura of Dassault Systemes Joins NuoDB Board of Directors Dassault Systèmes Announces the Acquisition of NuoDB, a Cloud-Native Distributed SQL Database Leader Deploy the NuoDB Database in Docker Containers NuoDB set to improve distributed SQL performance provided by Google News PlanetScale ends free tier bid, sheds staff in profitability bid PlanetScale forks MySQL to add vector support PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ... PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ... PlanetScale Insights Anomalies introduces smart query monitoring provided by Google News Automatically Generate Types for Your PostgreSQL Database Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora Why PostgreSQL Is the Bedrock for the Future of Data Crunchy Data Introduces Postgres Query Engine for Data Lakes, Crunchy Bridge for Analytics Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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