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ticktock | like time series database , with much better performance | Time Series Database library

 by   ytyou C++ Version: Current License: GPL-3.0

 by   ytyou C++ Version: Current License: GPL-3.0

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kandi X-RAY | ticktock Summary

ticktock is a C++ library typically used in Database, Time Series Database applications. ticktock has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
TickTock is an open source Time Series DataBase (TSDB) for DevOps, Internet of Things (IoT), and financial data. Based on many years of unsatisfied experience with TSDBs, we set our design goals of TickTock as:.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • ticktock has a low active ecosystem.
  • It has 14 star(s) with 1 fork(s). There are 6 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 0 open issues and 2 have been closed. On average issues are closed in 34 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of ticktock is current.
ticktock Support
Best in #Time Series Database
Average in #Time Series Database
ticktock Support
Best in #Time Series Database
Average in #Time Series Database

quality kandi Quality

  • ticktock has no bugs reported.
ticktock Quality
Best in #Time Series Database
Average in #Time Series Database
ticktock Quality
Best in #Time Series Database
Average in #Time Series Database

securitySecurity

  • ticktock has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
ticktock Security
Best in #Time Series Database
Average in #Time Series Database
ticktock Security
Best in #Time Series Database
Average in #Time Series Database

license License

  • ticktock is licensed under the GPL-3.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
ticktock License
Best in #Time Series Database
Average in #Time Series Database
ticktock License
Best in #Time Series Database
Average in #Time Series Database

buildReuse

  • ticktock releases are not available. You will need to build from source code and install.
  • Installation instructions, examples and code snippets are available.
ticktock Reuse
Best in #Time Series Database
Average in #Time Series Database
ticktock Reuse
Best in #Time Series Database
Average in #Time Series Database
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ticktock Key Features

Low resource requirement: It can run even with very low resources.

High performance: At least 10X better than OpenTSDB, competitive to the best TSDBs like InfluxDB.

Easy to install and maintain: Many TSDBs are built on top of other DBs, e.g., OpenTSDB on HBase, Clickhouse and Druid on relational DBs. This incurs complexity in installation and maintenance besides performance overhead. TickTock is natively developed in C++ and has a single process only. It doesn't require additional expertise like HBase for OpenTSDB in maintence. It doesn't have painful Garbage Collection issues to deal with in high load scenarios.

Replication and Scalability supports: TickTock provides replication and partition features in its open source versions.

Compatible with OpenTSDB APIs: OpenTSDB is one of the most widely used TSDBs. TickTock includes storing and querying APIs compatible with OpenTSDB. You can use OpenTSDB's TCollector to collect data and use Grafana to visualize data.

ticktock Examples and Code Snippets

See all related Code Snippets

To run TickTock Demo:

copy iconCopydownload iconDownload
docker run -d --name ticktock -p 3000:3000 -p 6181-6182:6181-6182 -p 6181:6181/udp ytyou/ticktock:latest-grafana

See all related Code Snippets

Community Discussions

Trending Discussions on Time Series Database
  • How do I instrument region and environment information correctly in Prometheus?
  • Amazon EKS (NFS) to Kubernetes pod. Can't mount volume
  • InfluxDB not starting: 8086 bind address already in use
  • Writing the data to the timeseries database over unstable network
  • Recommended approach to store multi-dimensional data (e.g. spectra) in InfluxDB
  • What to report in a time serie database when the measure failed?
  • R ggplot customize month labels in time series
  • How Can I Generate A Visualisation with Multiple Data Series In Splunk
  • How can I deploy QuestDB on GCP?
  • Group By day for custom time interval
Trending Discussions on Time Series Database

QUESTION

How do I instrument region and environment information correctly in Prometheus?

Asked 2022-Mar-09 at 17:53

I've an application, and I'm running one instance of this application per AWS region. I'm trying to instrument the application code with Prometheus metrics client, and will be exposing the collected metrics to the /metrics endpoint. There is a central server which will scrape the /metrics endpoints across all the regions and will store them in a central Time Series Database.

Let's say I've defined a metric named: http_responses_total then I would like to know its value aggregated over all the regions along with individual regional values. How do I store this region information which could be any one of the 13 regions and env information which could be dev or test or prod along with metrics so that I can slice and dice metrics based on region and env?

I found a few ways to do it, but not sure how it's done in general, as it seems a pretty common scenario:

I'm new to Prometheus. Could someone please suggest how I should store this region and env information? Are there any other better ways?

ANSWER

Answered 2022-Mar-09 at 17:53

All the proposed options will work, and all of them have downsides.

The first option (having env and region exposed by the application with every metric) is easy to implement but hard to maintain. Eventually somebody will forget to about these, opening a possibility for an unobserved failure to occur. Aside from that, you may not be able to add these labels to other exporters, written by someone else. Lastly, if you have to deal with millions of time series, more plain text data means more traffic.

The third option (storing these labels in a separate metric) will make it quite difficult to write and understand queries. Take this one for example:

sum by(instance) (node_arp_entries) and on(instance) node_exporter_build_info{version="0.17.0"}

It calculates a sum of node_arp_entries for instances with node-exporter version="0.17.0". Well more specifically it calculates a sum for every instance and then just drops those with a wrong version, but you got the idea.

The second option (adding these labels with Prometheus as a part of scrape configuration) is what I would choose. To save the words, consider this monitoring setup:

Datacener Prometheus Regional Prometheus Global Prometheus
1. Collects metrics from local instances. 2. Adds dc label to each metric. 3. Pushes the data into the regional Prometheus -> 1. Collects data on datacenter scale. 2. Adds region label to all metrics. 3. Pushes the data into the global instance -> Simply collects and stores the data on global scale

This is the kind of setup you need on Google scale, but the point is the simplicity. It's perfectly clear where each label comes from and why. This approach requires you to make Prometheus configuration somewhat more complicated, and the less Prometheus instances you have, the more scrape configurations you will need. Overall, I think, this option beats the alternatives.

Source https://stackoverflow.com/questions/71408188

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ticktock

We prepare a TickTock Demo in a docker image. With a single command to launch the docker, there will be a fully functional demo in the docker,.
A TickTock TSDB;
A Tcollector collecting OS metrics of the docker and sending to TickTock;
A Grafana providing metric dashboard to visualize the metrics.

Support

For more information, please refer to TickTock documentation.

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