DBMS > GridDB vs. HEAVY.AI vs. Neo4j vs. Quasardb

System Properties Comparison GridDB vs. HEAVY.AI vs. Neo4j vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Distributed, high-performance timeseries database

Primary database model

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS

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

Score	1.25
Rank	#157	Overall
	#12	Time Series DBMS

Score	1.48
Rank	#146	Overall
	#70	Relational DBMS

Score	59.35
Rank	#19	Overall
	#1	Graph DBMS

Score	0.07
Rank	#330	Overall
	#29	Time Series DBMS

Website

griddb.net

github.com/heavyai/heavydb
www.heavy.ai

neo4j.com

quasardb.net

Technical documentation

Developer

Toshiba Corporation

HEAVY.AI, Inc.

Neo4j, Inc.

quasardb

Initial release

2013

2016

2007

2009

Current release

4.6, February 2021

5.10, January 2022

4.4.9, July 2022

3.13.3, April 2022

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version3, commercial licenses available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

C++ and CUDA

Java, Scala

C++

Server operating systems

Linux

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

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

integer and binary

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

yes

with tags

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

JDBC
ODBC
Thrift
Vega

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

HTTP API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

yes using Neo4j Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Optimizes memory and compute layers to deliver unprecedented performance. Natively...
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Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Only HEAVY.AI allows users to visually and interactively discover high-value patterns,...
» more

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

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Advanced analytics, geospatial and time-series analytics, accelerated data science,...
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Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

GitHub trending repository
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Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

HEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more

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

News

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11 August 2022

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10 August 2022

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5 August 2022

Empowering Employees With Graph Technology
1 August 2022

This Week in Neo4j: Graph Data Science, Microservices, Java, Chatbot, PHP, Spring Data, and More
30 July 2022

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