DBMS > Amazon Aurora vs. Couchbase vs. CrateDB vs. IBM Db2 vs. PostgreSQL
System Properties Comparison Amazon Aurora vs. Couchbase vs. CrateDB vs. IBM Db2 vs. PostgreSQL
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Name | Amazon Aurora Xexclude from comparison | Couchbase Originally called Membase Xexclude from comparison | CrateDB Xexclude from comparison | IBM Db2 formerly named DB2 or IBM Database 2 Xexclude from comparison | PostgreSQL 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 | Distributed Database based on Lucene | Common in IBM host environments, 2 different versions for host and Windows/Linux | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Document store | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Relational DBMS Since Version 10.5 support for JSON/BSON documents compatible with MongoDB | 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 | 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 | Relational DBMS | Document store RDF store in Db2 LUW (Linux, Unix, Windows) Spatial DBMS with Db2 Spatial Extender | 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 | cratedb.com | www.ibm.com/products/db2 | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | docs.couchbase.com | cratedb.com/docs | www.ibm.com/docs/en/db2 | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Couchbase, Inc. | Crate | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2011 | 2013 | 1983 host version | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 12.1, October 2016 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source | commercial free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform. |
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Implementation language | C, C++, Go and Erlang | Java | C and C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X Windows | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | AIX HP-UX Linux Solaris Windows z/OS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | Flexible Schema (defined schema, partial schema, schema free) | 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. | yes | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes, but no triggers and constraints, and PostgreSQL compatibility | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | ADO.NET JDBC JSON style queries MongoDB compatible ODBC XQuery | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Erlang Go community maintained client Java JavaScript (Node.js) community maintained client Perl community maintained client PHP Python R Ruby community maintained client Scala community maintained client | C C# C++ Cobol Delphi Fortran Java Perl PHP Python Ruby Visual Basic | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | user defined functions (Javascript) | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes via the TAP protocol | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Automatic Sharding | Sharding | Sharding only with Windows/Unix/Linux Version | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | Multi-source replication including cross data center replication Source-replica replication | Configurable replication on table/partition-level | yes with separate tools (MQ, InfoSphere) | 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 | Eventual Consistency Read-after-write consistency on record level | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | ACID | 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. | yes | yes Ephemeral buckets | no | 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. | rights management via user accounts | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | Couchbase Originally called Membase | CrateDB | IBM Db2 formerly named DB2 or IBM Database 2 | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | Couchbase Originally called Membase | CrateDB | IBM Db2 formerly named DB2 or IBM Database 2 | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ... Join the preview of Amazon Aurora Limitless Database | Amazon Web Services Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ... 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 CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Announces Availability of CrateDB on Google Cloud Marketplace How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge provided by Google News Data migration strategies to Amazon RDS for Db2 | Amazon Web Services IBM Collaborates with AWS to Launch a New Cloud Database Offering, Enabling Customers to Optimize Data ... IBM's vintage Db2 database jumps on AWS's cloud bandwagon Precisely Supports Amazon RDS for Db2 Service with Real-Time Data Integration Capabilities Blog Theme - Details provided by Google News A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions 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 provided by Google News |
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