DBMS > AllegroGraph vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. MongoDB vs. Neo4j
System Properties Comparison AllegroGraph vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. MongoDB vs. Neo4j
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Name | AllegroGraph Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | MongoDB Xexclude from comparison | Neo4j Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | High performance, persistent RDF store with additional support for Graph DBMS | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Distributed Event Store optimized for Internet of Things use cases | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store with version 6.5 Graph DBMS RDF store Vector DBMS | Key-value store Wide column store | Event Store Time Series DBMS | Document store | Graph DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | allegrograph.com | cloud.google.com/bigtable | www.ibm.com/products/db2-event-store | www.mongodb.com | neo4j.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | franz.com/agraph/support/documentation/current/agraph-introduction.html | cloud.google.com/bigtable/docs | www.ibm.com/docs/en/db2-event-store | www.mongodb.com/docs/manual | neo4j.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Franz Inc. | IBM | MongoDB, Inc | Neo4j, Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2004 | 2015 | 2017 | 2009 | 2007 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.0, December 2023 | 2.0 | 6.0.7, June 2023 | 5.20, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Limited community edition free | commercial | commercial free developer edition available | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | Open Source GPL version3, commercial licenses available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no MongoDB available as DBaaS (MongoDB Atlas) | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C and C++ | C++ | Java, Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | Linux Linux, macOS, Windows for the developer addition | Linux OS X Solaris Windows | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes RDF schemas | schema-free | yes | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | schema-free and schema-optional | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | yes | yes string, integer, double, decimal, boolean, date, object_id, geospatial | 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 bulk load of XML files possible | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | no | yes | yes pluggable indexing subsystem, by default Apache Lucene | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SPARQL is used as query language | no | yes through the embedded Spark runtime | Read-only SQL queries via the MongoDB Atlas SQL Interface | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API SPARQL | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Clojure Java Lisp Perl Python Ruby Scala | C# C++ Go Java JavaScript (Node.js) Python | C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes JavaScript or Common Lisp | no | yes | JavaScript | yes User defined Procedures and Functions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | no | yes in MongoDB Atlas only | yes via event handler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | with Federation | Sharding | Sharding | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | yes using Neo4j Fabric | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication Source-replica replication | Internal replication in Colossus, and regional replication between two clusters in different zones | Active-active shard replication | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | Causal Clustering using Raft protocol available in in Enterprise Version only | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency depending on configuration | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Eventual Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no typically not used, however similar functionality with DBRef possible | yes Relationships in graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | no | Multi-document ACID Transactions with snapshot isolation | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | No - written data is immutable | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | yes optional, enabled by default | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | yes In-memory storage engine introduced with MongoDB version 3.2 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Users with fine-grained authorization concept, user roles and pluggable authentication | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | Access rights for users and roles | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
AllegroGraph | Google Cloud Bigtable | IBM Db2 Event Store | MongoDB | Neo4j | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and... » more | Built around the flexible document data model and unified API, MongoDB is a developer... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps Can Neuro-Symbolic AI Solve AI’s Weaknesses? 100 Companies That Matter in KM – Franz Inc. Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar) What is Neuro-Symbolic AI? | 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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AllegroGraph | Google Cloud Bigtable | IBM Db2 Event Store | MongoDB | Neo4j | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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