DBMS > Google BigQuery vs. Machbase Neo vs. Microsoft Access vs. Neo4j

System Properties Comparison Google BigQuery vs. Machbase Neo vs. Microsoft Access vs. Neo4j

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

TimeSeries DBMS for AIoT and BigData

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Primary database model

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Website

cloud.google.com/bigquery

machbase.com

www.microsoft.com/en-us/microsoft-365/access

neo4j.com

Technical documentation

cloud.google.com/bigquery/docs

machbase.com/dbms

developer.microsoft.com/en-us/access

neo4j.com/docs

Developer

Google

Machbase

Microsoft

Neo4j, Inc.

Initial release

2010

2013

1992

2007

Current release

V8.0, August 2023

1902 (16.0.11328.20222), March 2019

5.19, April 2024

License

Commercial or Open Source

commercial

free test version available

commercial

Bundled with Microsoft Office

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++

Java, Scala

Server operating systems

hosted

Linux
macOS
Windows

Windows

Not a real database server, but making use of DLLs

Linux

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

Data scheme

yes

schema-free and schema-optional

Typing

predefined data types such as float or date

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

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
DAO
ODBC
OLE DB

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

yes

User defined Procedures and Functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

simple password-based access control

a simple user-level security was built in till version Access 2003

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...
» more

Typical application scenarios

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

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.