DBMS > Drizzle vs. EsgynDB vs. Pinecone vs. RRDtool

System Properties Comparison Drizzle vs. EsgynDB vs. Pinecone vs. RRDtool

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A managed, cloud-native vector database

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

Relational DBMS

Vector DBMS

Time Series DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	1.70
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.esgyn.cn

www.pinecone.io

oss.oetiker.ch/rrdtool

Technical documentation

docs.pinecone.io/docs/overview

oss.oetiker.ch/rrdtool/doc

Developer

Drizzle project, originally started by Brian Aker

Esgyn

Pinecone Systems, Inc

Tobias Oetiker

Initial release

2008

2015

2019

1999

Current release

7.2.4, September 2012

1.8.0, 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

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

C++

C++, Java

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

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

HP-UX
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

Python

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

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

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

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

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Pinecone serverless goes multicloud as vector database market heats up
27 August 2024, VentureBeat

Using the Pinecone vector database in .NET
12 September 2024, InfoWorld

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone launches serverless vector database on Azure, GCP
27 August 2024, TechTarget

Pinecone Makes Accurate, Fast, Scalable Generative AI Accessible to Organizations Large and Small with Launch of its Serverless Vector Database
21 May 2024, PR Newswire

provided by Google News

SQLi vulnerability in Cacti could lead to RCE (CVE-2023-51448)
9 January 2024, Help Net Security

Critical IP spoofing bug patched in Cacti
15 December 2022, The Daily Swig

How to install Cacti SNMP Monitor on Ubuntu
24 November 2017, TechRepublic

The 16 Best Open Source Network Monitoring Tools in 2023
21 October 2022, Solutions Review

Cacti Cross-Site-Scripting Vulnerability Let Attacker Poison Database
7 September 2023, CybersecurityNews

provided by Google News

Share this page