DBMS > Bangdb vs. Google BigQuery vs. Immudb vs. Neo4j

System Properties Comparison Bangdb vs. Google BigQuery vs. Immudb vs. Neo4j

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Large scale data warehouse service with append-only tables

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

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
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Website

bangdb.com

cloud.google.com/bigquery

github.com/codenotary/immudb
immudb.io

neo4j.com

Technical documentation

docs.bangdb.com

cloud.google.com/bigquery/docs

docs.immudb.io

neo4j.com/docs

Developer

Sachin Sinha, BangDB

Google

Codenotary

Neo4j, Inc.

Initial release

2012

2010

2020

2007

Current release

BangDB 2.0, October 2021

1.2.3, April 2022

5.19, April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

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.

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

Implementation language

C, C++

Java, Scala

Server operating systems

Linux

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux

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

Data scheme

schema-free

yes

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like syntax

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

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++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
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

yes

User defined Procedures and Functions

Triggers

yes, Notifications (with Streaming only)

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

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)

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
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Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

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

Market metrics

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

Licensing and pricing models

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

News

This Week in Neo4j: GraphRAG, Knowledge Graphs, Open Source AI, GraphQL and more
4 May 2024

This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more
27 April 2024

GQL is Here: Your Cypher Queries in a GQL World
26 April 2024

GQL: The ISO Standard for Graphs Has Arrived
25 April 2024

What Is Retrieval-Augmented Generation (RAG)?
24 April 2024

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