DBMS > Amazon Redshift vs. Axibase vs. BigObject vs. Google Cloud Firestore vs. Neo4j

System Properties Comparison Amazon Redshift vs. Axibase vs. BigObject vs. Google Cloud Firestore vs. Neo4j

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Analytic DBMS for real-time computations and queries

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Graph DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	42.68
Rank	#21	Overall
	#1	Graph DBMS

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

bigobject.io

firebase.google.com/products/firestore

neo4j.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

firebase.google.com/docs/firestore

neo4j.com/docs

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

BigObject, Inc.

Google

Neo4j, Inc.

Initial release

2012

2013

2015

2017

2007

Current release

15585

5.23, August 2024

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community edition available

commercial

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

Java

Java, Scala

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux

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

Data scheme

yes

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

restricted

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
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

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Lua

yes, Firebase Rules & Cloud Functions

yes

User defined Procedures and Functions

Triggers

yes

yes, with Cloud Functions

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Multi-source replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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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...
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Licensing and pricing models

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