DBMS > Google BigQuery vs. GraphDB vs. Milvus vs. Neo4j vs. ToroDB

System Properties Comparison Google BigQuery vs. GraphDB vs. Milvus vs. Neo4j vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Website

cloud.google.com/bigquery

www.ontotext.com

milvus.io

neo4j.com

github.com/torodb/server

Technical documentation

cloud.google.com/bigquery/docs

graphdb.ontotext.com/documentation

milvus.io/docs/overview.md

neo4j.com/docs

Social network pages

Developer

Google

Ontotext

Neo4j, Inc.

8Kdata

Initial release

2010

2000

2019

2007

2016

Current release

10.4, October 2023

2.3.4, January 2024

5.20, May 2024

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

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

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java

C++, Go

Java, Scala

Java

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

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

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

yes

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

RESTful HTTP/JSON API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

well-defined plugin interfaces; JavaScript server-side extensibility

yes

User defined Procedures and Functions

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & 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

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Access rights for users and roles

More information provided by the system vendor

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

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

Highly available, versatile, and robust with millisecond latency. Supports batch...
» 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

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» 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

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» 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

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ 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

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

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6 June 2024

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31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more
8 June 2024

Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud
4 June 2024

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph
4 June 2024

This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more
1 June 2024

openCypher Will Pave the Road to GQL for Cypher Implementers
22 May 2024

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