DBMS > Apache Druid vs. Atos Standard Common Repository vs. BigchainDB vs. IRONdb vs. Snowflake

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. BigchainDB vs. IRONdb vs. Snowflake

Editorial information provided by DB-Engines

Name

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

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Document store

Time Series DBMS

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

druid.apache.org

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

www.bigchaindb.com

www.circonus.com/solutions/time-series-database/

www.snowflake.com

Technical documentation

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

docs.circonus.com/irondb/category/getting-started

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Atos Convergence Creators

Circonus LLC.

Snowflake Computing Inc.

Initial release

2012

2016

2017

2014

Current release

29.0.1, April 2024

1703

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

AGPL v3

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

C and C++

Server operating systems

Linux
OS X
Unix

Linux

hosted

Data scheme

yes

schema-less columns are supported

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

text, numeric, histograms

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 for querying

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

LDAP

CLI Client
RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

cell division

Sharding

Automatic, metric affinity per node

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

selectable replication factor

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency per node, eventual consistency across nodes

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

LDAP bind authentication

yes

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

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