DBMS > Amazon Redshift vs. Axibase vs. InfluxDB vs. Lovefield vs. RRDtool

System Properties Comparison Amazon Redshift vs. Axibase vs. InfluxDB vs. Lovefield vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

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.

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

oss.oetiker.ch/rrdtool

Technical documentation

docs.aws.amazon.com/redshift

docs.influxdata.com/influxdb

github.com/google/lovefield/blob/master/docs/spec_index.md

oss.oetiker.ch/rrdtool/doc

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

Google

Tobias Oetiker

Initial release

2012

2013

2014

1999

Current release

15585

2.7.6, April 2024

2.1.12, February 2017

1.8.0, 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

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

JavaScript

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

Server operating systems

hosted

Linux

Linux
OS X

through Homebrew

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

HP-UX
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

Numeric data and Strings

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

HTTP API
JSON over UDP

in-process shared library
Pipes

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

JavaScript

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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