DBMS > ArangoDB vs. Google BigQuery vs. Neo4j vs. PostgreSQL vs. Stardog
System Properties Comparison ArangoDB vs. Google BigQuery vs. Neo4j vs. PostgreSQL vs. Stardog
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Name | ArangoDB Xexclude from comparison | Google BigQuery Xexclude from comparison | Neo4j Xexclude from comparison | PostgreSQL Xexclude from comparison | Stardog Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language. | Large scale data warehouse service with append-only tables | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS Key-value store Search engine | Relational DBMS | Graph DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Graph DBMS RDF store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | arangodb.com | cloud.google.com/bigquery | neo4j.com | www.postgresql.org | www.stardog.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.arangodb.com | cloud.google.com/bigquery/docs | neo4j.com/docs | www.postgresql.org/docs | docs.stardog.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | ArangoDB Inc. | Neo4j, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | Stardog-Union | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2010 | 2007 | 1989 1989: Postgres, 1996: PostgreSQL | 2010 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 3.11.5, November 2023 | 5.20, May 2024 | 16.3, May 2024 | 7.3.0, May 2020 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; Commercial license (Enterprise) available | commercial | Open Source GPL version3, commercial licenses available | Open Source BSD | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. |
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Implementation language | C++ | Java, Scala | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux macOS Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free automatically recognizes schema within a collection | yes | schema-free and schema-optional | yes | schema-free and OWL/RDFS-schema support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes string, double, boolean, list, hash | 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. | no | yes specific XML-type available, but no XML query functionality. | no Import/export of XML data possible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes pluggable indexing subsystem, by default Apache Lucene | yes | yes supports real-time indexing in full-text and geospatial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | yes | no | yes standard with numerous extensions | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | AQL Foxx Framework Graph API (Gremlin) GraphQL query language HTTP API Java & SpringData JSON style queries VelocyPack/VelocyStream | RESTful HTTP/JSON API | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | ADO.NET JDBC native C library ODBC streaming API for large objects | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Clojure Elixir Go Java JavaScript (Node.js) PHP Python R Rust | .Net Java JavaScript Objective-C PHP Python Ruby | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | .Net Clojure Groovy Java JavaScript Python Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | JavaScript | user defined functions in JavaScript | yes User defined Procedures and Functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | user defined functions and aggregates, HTTP Server extensions in Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes via event handler | yes | yes via event handlers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding since version 2.0 | none | yes using Neo4j Fabric | partitioning by range, list and (since PostgreSQL 11) by hash | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication with configurable replication factor | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication in HA-Cluster | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no can be done with stored procedures in JavaScript | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency configurable per collection or per write Immediate Consistency OneShard (highly available, fault-tolerant deployment mode with ACID semantics) | Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | Immediate Consistency in HA-Cluster | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes relationships in graphs | no | yes Relationships in graphs | yes | yes relationships in graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no Since BigQuery is designed for querying data | ACID | 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. | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | Access privileges (owner, writer, reader) on dataset, table or view level Google Cloud Identity & Access Management (IAM) | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | fine grained access rights according to SQL-standard | Access rights for users and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ArangoDB | Google BigQuery | Neo4j | PostgreSQL | Stardog | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Consolidation: As a native multi-model database, can be used as a full blown document... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Native multi-model in ArangoDB is being used for a broad range of projects across... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | ArangoDB is the leading native multi-model database with over 11,000 stargazers on... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Very permissive Apache 2 License for Community Edition & commercial licenses are... » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more openCypher Will Pave the Road to GQL for Cypher Implementers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ArangoDB | Google BigQuery | Neo4j | PostgreSQL | Stardog | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | The Weight of Relational Databases: Time for Multi-Model? | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Cloud-based DBMS's popularity grows at high rates | Applying Graph Analytics to Game of Thrones MySQL, PostgreSQL and Redis are the winners of the March ranking The openCypher Project: Help Shape the SQL for Graphs | 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 | ArangoGraphML: Simplifying the Power of Graph Machine Learning How to Build Knowledge Graph Enhanced Chatbot with ChatGPT and ArangoDB ArangoDB brings yet more money into graph database market with $27.8M round ArangoDB expands scope of graph database platform Open source graph database company ArangoDB raises $27.8M provided by Google News | Winning the 2020 Google Cloud Technology Partner of the Year – Infrastructure Modernization Award Google Cloud partners Coinbase to accept crypto payments Hightouch Raises $38M in Funding provided by Google News | Neo4j graph analytics integrated with Snowflake's AI cloud – Blocks and Files Neo4j integrates dozens of graph analytics functions with data in Snowflake Neo4j & Snowflake Collaborate for AI Insights & Analytics Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Neo4j Partners with Snowflake for Advanced AI Insights and Predictive Analytics provided by Google News | PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL How To Schedule PostgreSQL Backups With GitHub Actions How to implement a better like, views, comment counters in PostgreSQL? Enterprise DB begins rolling AI features into PostgreSQL provided by Google News |
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