DBMS > Atos Standard Common Repository vs. ClickHouse vs. GridDB vs. Neo4j vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. ClickHouse vs. GridDB vs. Neo4j vs. Snowflake

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Secondary database models

Time Series DBMS

Key-value store
Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

Technical documentation

clickhouse.com/docs

docs.griddb.net

neo4j.com/docs

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Clickhouse Inc.

Toshiba Corporation

Neo4j, Inc.

Snowflake Computing Inc.

Initial release

2016

2013

2007

2014

Current release

1703

v24.4.1.2088-stable, May 2024

5.1, August 2022

5.19, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

Open Source

GPL version3, commercial licenses available

commercial

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

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

Implementation language

Java

C++

Java, Scala

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux

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

hosted

Data scheme

Schema and schema-less with LDAP views

yes

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

optional

yes

numerical, string, blob, geometry, boolean, timestamp

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.

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

LDAP

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

user defined functions

Triggers

yes

via event handler

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

key based and custom

Sharding

yes using Neo4j Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

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

yes

Transaction concepts

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

Atomic execution of specific operations

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

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

LDAP bind authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per database

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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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Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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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.
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Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

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

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

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