DBMS > Graphite vs. JaguarDB vs. Sequoiadb vs. Tkrzw vs. Yaacomo

System Properties Comparison Graphite vs. JaguarDB vs. Sequoiadb vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Performant, highly scalable DBMS for AI and IoT applications

NewSQL database with distributed OLTP and SQL

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Key-value store
Vector DBMS

Document store
Relational DBMS

Key-value store

Relational DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

github.com/graphite-project/graphite-web

www.jaguardb.com

www.sequoiadb.com

dbmx.net/tkrzw

yaacomo.com

Technical documentation

graphite.readthedocs.io

www.jaguardb.com/support.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Chris Davis

DataJaguar, Inc.

Sequoiadb Ltd.

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2006

2015

2013

2020

2009

Current release

3.3 July 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Python

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
Unix

Linux

Linux
macOS

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

HTTP API
Sockets

JDBC
ODBC

proprietary protocol using JSON

JDBC
ODBC

Supported programming languages

JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

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

using specific database classes

yes

User concepts

Access control

rights management via user accounts

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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