DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. BigchainDB vs. RavenDB vs. Snowflake

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. BigchainDB vs. RavenDB vs. Snowflake

Editorial information provided by DB-Engines

Name

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

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Time Series DBMS

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

iotdb.apache.org

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

www.bigchaindb.com

ravendb.net

www.snowflake.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

bigchaindb.readthedocs.io/en/latest

ravendb.net/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Atos Convergence Creators

Hibernating Rhinos

Snowflake Computing Inc.

Initial release

2018

2016

2010

2014

Current release

1.1.0, April 2023

1703

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

AGPL v3

Open Source

AGPL version 3, commercial license 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.

Implementation language

Java

Python

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
macOS
Raspberry Pi
Windows

hosted

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

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

Typing

predefined data types such as float or date

yes

optional

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 language

SQL-like query language (RQL)

yes

APIs and other access methods

JDBC
Native API

LDAP

CLI Client
RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

cell division

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

selectable replication factor

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency or Eventual Consistency depending on configuration

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

LDAP bind authentication

yes

Authorization levels configured per client per database

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

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