DBMS > Apache IoTDB vs. Faircom EDGE vs. GraphDB vs. Memgraph vs. Neo4j
System Properties Comparison Apache IoTDB vs. Faircom EDGE vs. GraphDB vs. Memgraph vs. Neo4j
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Name | Apache IoTDB Xexclude from comparison | Faircom EDGE formerly c-treeEDGE Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Memgraph Xexclude from comparison | Neo4j Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink | FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments | 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. | An open source graph database built for real-time streaming and compatible with Neo4j | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series DBMS | Key-value store Relational DBMS | Graph DBMS RDF store | Graph DBMS | Graph DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | iotdb.apache.org | www.faircom.com/products/faircom-edge | www.ontotext.com | memgraph.com | neo4j.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html | docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html | graphdb.ontotext.com/documentation | memgraph.com/docs | neo4j.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | Apache Software Foundation | FairCom Corporation | Ontotext | Memgraph Ltd | Neo4j, Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 1979 | 2000 | 2017 | 2007 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.1.0, April 2023 | V3, October 2020 | 10.4, October 2023 | 5.20, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | commercial Restricted, free version available | commercial Some plugins of GraphDB Workbench are open sourced | Open Source BSL 1.1; commercial license for enterprise edition available | Open Source GPL version3, commercial licenses available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | ANSI C, C++ | Java | C and C++ | Java, Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM (>= 1.8) | Android Linux ARM, x86 Raspbian Windows | All OS with a Java VM Linux OS X Windows | Linux | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | Flexible Schema (defined schema, partial schema, schema free) | schema-free and OWL/RDFS-schema support; RDF shapes | schema-free and schema-optional | schema-free and schema-optional | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes, ANSI Standard SQL Types | 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 | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes pluggable indexing subsystem, by default Apache Lucene | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | yes ANSI SQL queries | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Native API | ADO.NET Direct SQL IoT Microservice layer JDBC MQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | Bolt protocol Cypher query language | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Go Java Python Scala | C C# C++ Java JavaScript PHP Python VB.Net | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | .Net C C++ Elixir Go Haskell Java JavaScript PHP Python Ruby Scala | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | yes .Net, JavaScript, C/C++ | well-defined plugin interfaces; JavaScript server-side extensibility | yes User defined Procedures and Functions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes | no | yes via event handler | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning (by time range) + vertical partitioning (by deviceId) | File partitioning Customizable business rules for partitioning | none | Sharding dynamic graph partitioning | yes using Neo4j Fabric | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas | yes Synchronous and asynchronous realtime replication based on transaction logs | Multi-source replication | Multi-source replication using RAFT | Causal Clustering using Raft protocol available in in Enterprise Version only | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Integration with Hadoop and Spark | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Strong Consistency with Raft | Immediate Consistency Tunable Consistency | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes when using SQL | yes Constraint checking | yes relationships in graphs | yes Relationships in graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID | ACID with snapshot isolation | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes across SQL and NoSQL | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes with periodic snapshot and write-ahead logging (WAL) of changes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL. | 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. | Users, roles and permissions | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache IoTDB | Faircom EDGE formerly c-treeEDGE | GraphDB former name: OWLIM | Memgraph | Neo4j | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | Memgraph directly connects to your streaming infrastructure so you and your team... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | Business Source License ensures a future for the Memgraph community MAGE algorithm... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | Graph algorithms in bioinformatics Social network analysis Cryptocurrency network... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | You can check out our pricing model and licenses on the company website . » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Integrating GraphDB with Relational Database Systems Understanding the Graph Center of Excellence Migrating From LPG to RDF Graph Model Case study: Policy Enforcement Automation With Semantics Okay, RAG… We Have a Problem | openCypher Will Pave the Road to GQL for Cypher Implementers 7 Tips for Submitting Your NODES 2024 Talk How to Configure Neo4j Aura With AWS PrivateLink This Week in Neo4j: Podcast, GraphRAG, GraphQL, Chatbot and more Neo4j Joins the Connect with Confluent Partner Program | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache IoTDB | Faircom EDGE formerly c-treeEDGE | GraphDB former name: OWLIM | Memgraph | Neo4j | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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