DBMS > Amazon Redshift vs. Apache Phoenix vs. BigchainDB vs. RRDtool vs. Yanza

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. BigchainDB vs. RRDtool vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Large scale data warehouse service for use with business intelligence tools

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/redshift

phoenix.apache.org

www.bigchaindb.com

oss.oetiker.ch/rrdtool

yanza.com

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

bigchaindb.readthedocs.io/en/latest

oss.oetiker.ch/rrdtool/doc

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Tobias Oetiker

Yanza

Initial release

2012

2014

2016

1999

2015

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL v3

Open Source

GPL V2 and FLOSS

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Python

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
Unix
Windows

Linux

HP-UX
Linux

Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC

CLI Client
RESTful HTTP API

in-process shared library
Pipes

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

fine grained access rights according to SQL-standard

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

yes

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