DBMS > Atos Standard Common Repository vs. Google Cloud Firestore vs. NCache vs. Snowflake vs. TerarkDB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Firestore vs. NCache vs. Snowflake vs. TerarkDB

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

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.

Open-Source and Enterprise in-memory Key-Value Store

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

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

firebase.google.com/products/firestore

www.alachisoft.com/ncache

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

firebase.google.com/docs/firestore

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Atos Convergence Creators

Google

Alachisoft

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2016

2017

2005

2014

2016

Current release

1703

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

commercial

restricted open source version 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.

Implementation language

Java

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux

hosted

Linux
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

optional

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

APIs and other access methods

LDAP

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages with LDAP bindings

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

yes

yes, with Cloud Functions

yes

Notifications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes, with selectable consistency level

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

optimistic locking and pessimistic locking

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

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

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

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Market metrics

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Licensing and pricing models

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