DBMS > BoltDB vs. HugeGraph vs. Neo4j vs. RocksDB vs. Weaviate

System Properties Comparison BoltDB vs. HugeGraph vs. Neo4j vs. RocksDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

github.com/boltdb/bolt

github.com/hugegraph
hugegraph.apache.org

neo4j.com

rocksdb.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

hugegraph.apache.org/docs

neo4j.com/docs

github.com/facebook/rocksdb/wiki

weaviate.io/developers/weaviate

Developer

Baidu

Neo4j, Inc.

Facebook, Inc.

Weaviate B.V.

Initial release

2013

2018

2007

2013

2019

Current release

0.9

5.20, May 2024

9.2.1, May 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

Open Source

BSD

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

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

Java, Scala

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Unix

Linux

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

Linux

Data scheme

schema-free

yes

schema-free and schema-optional

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

also supports composite index and range index

yes

pluggable indexing subsystem, by default Apache Lucene

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

GraphQL is used as query language

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

C++ API
Java API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Groovy
Java
Python

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

C
C++
Go
Java
Perl
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

User defined Procedures and Functions

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

yes using Neo4j Fabric

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

yes

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

Users, roles and permissions

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

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

All companies that have data.
» more

Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

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

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.