DBMS > Amazon Redshift vs. Apache Phoenix vs. RRDtool vs. Sphinx

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. RRDtool vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Time Series DBMS

Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/redshift

phoenix.apache.org

oss.oetiker.ch/rrdtool

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

oss.oetiker.ch/rrdtool/doc

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Tobias Oetiker

Sphinx Technologies Inc.

Initial release

2012

2014

1999

2001

Current release

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

1.8.0, 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

Open Source

GPL version 2, commercial licence 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

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

C++

Server operating systems

hosted

Linux
Unix
Windows

HP-UX
Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

JDBC

in-process shared library
Pipes

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

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

The original contents of fields are not stored in the Sphinx index.

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

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