DBMS > Google BigQuery vs. Graph Engine vs. IBM Db2 Event Store vs. Neo4j

System Properties Comparison Google BigQuery vs. Graph Engine vs. IBM Db2 Event Store vs. Neo4j

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Distributed Event Store optimized for Internet of Things use cases

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Event Store
Time Series DBMS

Graph DBMS

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Website

cloud.google.com/bigquery

www.graphengine.io

www.ibm.com/products/db2-event-store

neo4j.com

Technical documentation

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

www.ibm.com/docs/en/db2-event-store

neo4j.com/docs

Developer

Google

Microsoft

IBM

Neo4j, Inc.

Initial release

2010

2017

2007

Current release

2.0

5.19, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free developer edition available

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

.NET and C

C and C++

Java, Scala

Server operating systems

hosted

.NET

Linux

Linux, macOS, Windows for the developer addition

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

through the embedded Spark runtime

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
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

C#
C++
F#
Visual Basic

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.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

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

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

Eventual 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

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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)

fine grained access rights according to SQL-standard

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...
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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...
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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

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