DBMS > Amazon Neptune vs. Couchbase vs. Cubrid vs. InfinityDB vs. PostgreSQL
System Properties Comparison Amazon Neptune vs. Couchbase vs. Cubrid vs. InfinityDB vs. PostgreSQL
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| Name | Amazon Neptune Xexclude from comparison | Couchbase  Originally called Membase Xexclude from comparison | Cubrid Xexclude from comparison | InfinityDB Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Fast, reliable graph database built for the cloud | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP | A Java embedded Key-Value Store which extends the Java Map interface | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Graph DBMS RDF store | Document store | Relational DBMS | Key-value store | 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 Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/neptune | www.couchbase.com | cubrid.com (korean) cubrid.org (english) | boilerbay.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | aws.amazon.com/neptune/developer-resources | docs.couchbase.com | cubrid.org/manuals | boilerbay.com/infinitydb/manual | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Couchbase, Inc. | CUBRID Corporation, CUBRID Foundation | Boiler Bay Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2017 | 2011 | 2008 | 2002 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 11.0, January 2021 | 4.0 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source Apache Version 2.0 | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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, C++, Java | Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux OS X Windows | Linux Windows | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | yes | yes nested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | yes all Java primitives, Date, CLOB, BLOB, huge sparse arrays | 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 | no | yes | yes | no manual creation possible, using inversions based on multi-value capability | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes | no | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | OpenCypher RDF 1.1 / SPARQL 1.1 TinkerPop Gremlin | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET JDBC ODBC OLE DB | Access via java.util.concurrent.ConcurrentNavigableMap Interface Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm) | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C# Go Java JavaScript PHP Python Ruby Scala | .Net C Go Java JavaScript Node.jsKotlin PHP Python Ruby Scala | C C# C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | Java | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | Java Stored Procedures | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes via the TAP protocol | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Automatic Sharding | none | none | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances. | Multi-source replication including cross data center replication Source-replica replication | Source-replica replication | none | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Immediate Consistency | Immediate Consistency READ-COMMITTED or SERIALIZED | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes Relationships in graphs | no | yes | no manual creation possible, using inversions based on multi-value capability | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | ACID Optimistic locking for transactions; no isolation for bulk loads | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes with encyption-at-rest | 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 | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | fine grained access rights according to SQL-standard | no | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon Neptune | Couchbase Originally called Membase | Cubrid | InfinityDB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | 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 Exploring new features of Apache TinkerPop 3.7.x in Amazon Neptune | Amazon Web Services Building NHM London's Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS ... ADP Neptune Case Study Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services AWS announces Amazon Neptune I/O-Optimized provided by Google News Database company Couchbase cruises to another solid earnings and revenue beat A Closer Look at 9 Analyst Recommendations For Couchbase Couchbase (NASDAQ:BASE) Posts Better-Than-Expected Sales In Q1, Next Quarter's Growth Looks Optimistic Couchbase, Inc. (NASDAQ:BASE) Shares Slammed 29% But Getting In Cheap Might Be Difficult Regardless Couchbase, Inc. (BASE) Tops Q1 EPS by 5c; offers outlook 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 How To Schedule PostgreSQL Backups With GitHub Actions Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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