DBMS > Amazon DynamoDB vs. GraphDB vs. Milvus vs. PostgreSQL vs. Riak KV
System Properties Comparison Amazon DynamoDB vs. GraphDB vs. Milvus vs. PostgreSQL vs. Riak KV
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Name | Amazon DynamoDB Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Milvus Xexclude from comparison | PostgreSQL Xexclude from comparison | Riak KV Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Hosted, scalable database service by Amazon with the data stored in Amazons cloud | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | 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 | Distributed, fault tolerant key-value store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Key-value store | Graph DBMS RDF 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. | Key-value store with links between data sets and object tags for the creation of secondary indexes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/dynamodb | www.ontotext.com | milvus.io | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/dynamodb | graphdb.ontotext.com/documentation | milvus.io/docs/overview.md | www.postgresql.org/docs | www.tiot.jp/riak-docs/riak/kv/latest | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Social network pages | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Ontotext | PostgreSQL Global Development Group www.postgresql.org/developer | OpenSource, formerly Basho Technologies | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2000 | 2019 | 1989 1989: Postgres, 1996: PostgreSQL | 2009 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 10.4, October 2023 | 2.3.4, January 2024 | 16.3, May 2024 | 3.2.0, December 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free tier for a limited amount of database operations | commercial Some plugins of GraphDB Workbench are open sourced | Open Source Apache Version 2.0 | Open Source BSD | Open Source Apache version 2, commercial enterprise edition | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | Zilliz Cloud – Cloud-native service for Milvus |
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Implementation language | Java | C++, Go | C | Erlang | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | All OS with a Java VM Linux OS X Windows | Linux macOS 10.14 or later Windows with WSL 2 enabled | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free and OWL/RDFS-schema support; RDF shapes | yes | schema-free | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | Vector, Numeric and String | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes specific XML-type available, but no XML query functionality. | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | no | yes | restricted | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | no | yes standard with numerous extensions | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | HTTP API Native Erlang Interface | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net ColdFusion Erlang Groovy Java JavaScript Perl PHP Python Ruby | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | C++ Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C unofficial client library C# C++ unofficial client library Clojure unofficial client library Dart unofficial client library Erlang Go unofficial client library Groovy unofficial client library Haskell unofficial client library Java JavaScript unofficial client library Lisp unofficial client library Perl unofficial client library PHP Python Ruby Scala unofficial client library Smalltalk unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | well-defined plugin interfaces; JavaScript server-side extensibility | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Erlang | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by integration with AWS Lambda | no | no | yes | yes pre-commit hooks and post-commit hooks | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | none | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding no "single point of failure" | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Multi-source replication | Source-replica replication other methods possible by using 3rd party extensions | selectable replication factor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no may be implemented via Amazon Elastic MapReduce (Amazon EMR) | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be specified for read operations | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Bounded Staleness Eventual Consistency Immediate Consistency Session Consistency Tunable Consistency | Immediate Consistency | Eventual Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes Constraint checking | no | yes | no links between data sets can be stored | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID ACID across one or more tables within a single AWS account and region | ACID | no | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | Role based access control and fine grained access rights | fine grained access rights according to SQL-standard | yes, using Riak Security | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | GraphDB former name: OWLIM | Milvus | PostgreSQL | Riak KV | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | Milvus is an open-source and cloud-native vector database built for production-ready... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | Highly available, versatile, and robust with millisecond latency. Supports batch... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | RAG: retrieval augmented generation Video media : video understanding, video deduplication.... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Riding the Databricks Wave with Hybrid Knowledge Graphs Matching Skills and Candidates with Graph RAG A Triple Store RAG Retriever Integrating GraphDB with Relational Database Systems Understanding the Graph Center of Excellence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon DynamoDB | GraphDB former name: OWLIM | Milvus | PostgreSQL | Riak KV | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 Increased popularity for consuming DBMS services out of the cloud | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services provided by Google News | Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace Ontotext Announces Latest Major Release, GraphDB 10 Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer GraphDB Goes Open Source 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 | 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 | Basho Revamps Riak Open-Source Database A Critique of Resizable Hash Tables: Riak Core & Random Slicing Riak NoSQL snapped up by Bet365 Basho to Bolster Riak with DB Plug-Ins Basho Advances NoSQL Riak Enterprise 2.0 With Search, Advanced Data Types provided by Google News |
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