DBMS > Amazon DocumentDB vs. AnzoGraph DB vs. Fauna vs. IBM Db2 Event Store vs. PostgreSQL
System Properties Comparison Amazon DocumentDB vs. AnzoGraph DB vs. Fauna vs. IBM Db2 Event Store vs. PostgreSQL
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| Name | Amazon DocumentDB Xexclude from comparison | AnzoGraph DB Xexclude from comparison | Fauna  previously named FaunaDB Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Fast, scalable, highly available, and fully managed MongoDB-compatible database service | Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization | Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure. | Distributed Event Store optimized for Internet of Things use cases | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store | Graph DBMS RDF store | Document store Graph DBMS Relational DBMS Time Series DBMS | Event Store Time Series 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 | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/documentdb | cambridgesemantics.com/anzograph | fauna.com | www.ibm.com/products/db2-event-store | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | aws.amazon.com/documentdb/resources | docs.cambridgesemantics.com/anzograph/userdoc/home.htm | docs.fauna.com | www.ibm.com/docs/en/db2-event-store | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Cambridge Semantics | Fauna, Inc. | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2019 | 2018 | 2014 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.3, January 2021 | 2.0 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | commercial free trial version available | commercial | commercial free developer edition available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Scala | C and C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux | hosted | Linux Linux, macOS, Windows for the developer addition | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | Schema-free and OWL/RDFS-schema support | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | 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 | no | no | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | no | SPARQL and SPARQL* as primary query language. Cypher preview. | no | yes through the embedded Spark runtime | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | proprietary protocol using JSON (MongoDB compatible) | Apache Mule gRPC JDBC Kafka OData access for BI tools OpenCypher RESTful HTTP API SPARQL | RESTful HTTP API | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | Go Java JavaScript (Node.js) PHP Python | C++ Java Python | C# Go Java JavaScript Python Ruby Scala Swift | C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | user defined functions and aggregates | user defined functions | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Automatic sharding | horizontal partitioning consistent hashing | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas | Multi-source replication in MPP-Cluster | Multi-source replication | Active-active shard replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | Kerberos/HDFS data loading | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency in MPP-Cluster | Immediate Consistency | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no typically not used, however similar functionality with DBRef possible | no not needed in graphs | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic single-document operations | ACID | ACID | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | No - written data is immutable | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles | Access rights for users and roles | Identity management, authentication, and access control | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon DocumentDB | AnzoGraph DB | Fauna previously named FaunaDB | IBM Db2 Event Store | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | 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 Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services AWS announces Amazon DocumentDB I/O-Optimized Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services Game Developer's Guide to Amazon DocumentDB (with MongoDB compatibility) Part Three: Operation Best Practices ... provided by Google News AnzoGraph review: A graph database for deep analytics Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury Back to the future: Does graph database success hang on query language? Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable? provided by Google News Slicing the Gordian Knot: A leap to real-time systems of truth Fauna Launches Distributed Document-Relational Database On Google Cloud Marketplace Fauna Adds Transformative Schema-as-Code Capabilities to Enterprise Proven, Document-Relational Database Utah Natural Heritage Program Fauna Query Language tamed to appeal to developers provided by Google News The vision for Db2 Advancements in streaming data storage, real-time analysis and machine learning IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere How IBM Is Turning Db2 into an 'AI Database' Best cloud databases of 2022 provided by Google News At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Nutanix partners with EDB to fit database service for AI – Blocks and Files Nutanix and EDB Partner to Deliver a Modern Data Platform Let PostgreSQL Pick An Index For You Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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