DBMS > Couchbase vs. Milvus vs. PostgreSQL vs. Solr vs. YugabyteDB
System Properties Comparison Couchbase vs. Milvus vs. PostgreSQL vs. Solr vs. YugabyteDB
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| Name | Couchbase  Originally called Membase Xexclude from comparison | Milvus Xexclude from comparison | PostgreSQL Xexclude from comparison | Solr Xexclude from comparison | YugabyteDB 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 | A DBMS designed for efficient storage of vector data and vector similarity searches | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | A widely used distributed, scalable search engine based on Apache Lucene | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store | Vector DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Search engine | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Spatial DBMS | Document store Wide column store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.couchbase.com | milvus.io | www.postgresql.org | solr.apache.org | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.couchbase.com | milvus.io/docs/overview.md | www.postgresql.org/docs | solr.apache.org/resources.html | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Couchbase, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | Apache Software Foundation | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 2019 | 1989 1989: Postgres, 1996: PostgreSQL | 2006 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 2.4.4, May 2024 | 16.3, May 2024 | 9.6.1, May 2024 | 2.19, September 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source Apache Version 2.0 | Open Source BSD | Open Source Apache Version 2 | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Zilliz Cloud – Cloud-native service for Milvus |
| YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C, C++, Go and Erlang | C++, Go | C | Java | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Windows | Linux macOS 10.14 or laterWindows with WSL 2 enabled | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | yes Dynamic Fields enables on-the-fly addition of new fields | depending on used data model | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | Vector, Numeric and String | yes | yes supports customizable data types and automatic typing | 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 specific XML-type available, but no XML query functionality. | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes | yes All search fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | no | yes standard with numerous extensions | Solr Parallel SQL Interface | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API RESTful HTTP/JSON API | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C Go Java JavaScript Node.jsKotlin PHP Python Ruby Scala | C++ Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Java plugins | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes via the TAP protocol | no | yes | yes User configurable commands triggered on index changes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Automatic Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication including cross data center replication Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | yes | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | no | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Bounded Staleness Eventual Consistency Immediate Consistency Session Consistency Tunable Consistency | Immediate Consistency | Eventual Consistency | Strong consistency on writes and tunable consistency on reads | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | ACID | optimistic locking | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes Ephemeral buckets | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | Role based access control and fine grained access rights | fine grained access rights according to SQL-standard | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Couchbase Originally called Membase | Milvus | PostgreSQL | Solr | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Milvus is an open-source and cloud-native vector database built for production-ready... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Highly available, versatile, and robust with millisecond latency. Supports batch... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | RAG: retrieval augmented generation Video media : video understanding, video deduplication.... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise... » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed... » more | Apache 2.0 license for the database » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Couchbase Originally called Membase | Milvus | PostgreSQL | Solr | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | Vector databases | 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 | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | Database company Couchbase cruises to another solid earnings and revenue beat Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase (BASE) To Report Earnings Tomorrow: Here Is What To Expect Couchbase Server and Capella to gain vector support Couchbase, Inc. (BASE) Tops Q1 EPS by 5c; offers outlook provided by Google News | How NVIDIA GPU Acceleration Supercharged Milvus Vector Database AI-Powered Search Engine With Milvus Vector Database on Vultr Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search Zilliz Unveils Game-Changing Features for Vector Search IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI 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 PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL How to implement a better like, views, comment counters in PostgreSQL? provided by Google News | SOLR-led walkout demands better conditions for Compass workers Solr Network Launches Groundbreaking Solana Token Creator (SOLR) Technical Data SOLR hosts teach-in of labor movements at Northwestern Top 5 stock gainers and losers: SOLR.V, GRSL.V, ANON.C provided by Google News | YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... Yugabyte Named in the 2023 Gartner® Magic Quadrant™ for Cloud Database Management Systems The surprising link between Formula One and enterprise PostgreSQL optimisation 5 minutes with: David Walker, Field CTO, EMEA at Yugabyte provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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