DBMS > NSDb vs. Prometheus vs. Tkrzw

System Properties Comparison NSDb vs. Prometheus vs. Tkrzw

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Open-source Time Series DBMS and monitoring system

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

Primary database model

Time Series DBMS

Key-value store

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

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

Website

nsdb.io

prometheus.io

dbmx.net/tkrzw

Technical documentation

nsdb.io/Architecture

prometheus.io/docs

Developer

Mikio Hirabayashi

Initial release

2017

2015

2020

Current release

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Java, Scala

C++

Server operating systems

Linux
macOS

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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.

Import of XML data possible

Secondary indexes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP/JSON API

Supported programming languages

Java
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Using Apache Lucene

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

User concepts

Access control

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

Recent citations in the news

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

Exadata Real-Time Insight - Quick Start
3 April 2024, Oracle

OpenTelemetry vs. Prometheus: You can’t fix what you can’t see
29 March 2024, IBM

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

provided by Google News

Share this page